# site_config

key: description
value:
Website at https://opening-up-chatgpt.github.io/ Source at https://github.com/opening-up-chatgpt/ Data License https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io/blob/main/projects/A_sample.yaml


# type

id: projects
directory: projects
list_fields: ["project_name"]
default_format: yaml
json_schema:
{"type": "object", "properties": {"project": {"type": "object", "properties": {"name": {"type": "string", "title": "Project Name", "description": ""}, "link": {"type": "string", "format": "uri", "title": "Project Link", "description": ""}, "notes": {"type": "string", "title": "Project Notes", "description": ""}, "llmbase": {"type": "string", "title": "Project llmbase", "description": ""}, "rlbase": {"type": "string", "title": "Project rlbase", "description": ""}, "license": {"type": "string", "title": "Project license", "description": ""}}}, "org": {"type": "object", "properties": {"name": {"type": "string", "title": "Org Name", "description": ""}, "link": {"type": "string", "format": "uri", "title": "Org link", "description": ""}, "notes": {"type": "string", "title": "Org notes", "description": ""}}}, "opencode": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability Open Code Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability Open Code link", "description": ""}, "notes": {"type": "string", "title": "Availability Open Code notes", "description": ""}}}, "llmdata": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability LLM Data Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability LLM Data link", "description": ""}, "notes": {"type": "string", "title": "Availability LLM Data notes", "description": ""}}}, "llmweights": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability LLM Weights Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability LLM Weights link", "description": ""}, "notes": {"type": "string", "title": "Availability LLM Weights notes", "description": ""}}}, "rldata": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability RL Data Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability RL Data link", "description": ""}, "notes": {"type": "string", "title": "Availability RL Data notes", "description": ""}}}, "rlweights": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability RL Weights Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability RL Weights link", "description": ""}, "notes": {"type": "string", "title": "Availability RL Weights notes", "description": ""}}}, "license": {"type": "object", "properties": {"class": {"type": "string", "title": "Availability License Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Availability License link", "description": ""}, "notes": {"type": "string", "title": "Availability License notes", "description": ""}}}, "code": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Code Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Code link", "description": ""}, "notes": {"type": "string", "title": "Documentation Code notes", "description": ""}}}, "architecture": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Architecture Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Architecture link", "description": ""}, "notes": {"type": "string", "title": "Documentation Architecture notes", "description": ""}}}, "preprint": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Preprint Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Preprint link", "description": ""}, "notes": {"type": "string", "title": "Documentation Preprint notes", "description": ""}}}, "paper": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Paper Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Paper link", "description": ""}, "notes": {"type": "string", "title": "Documentation Paper notes", "description": ""}}}, "modelcard": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Modelcard Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Modelcard link", "description": ""}, "notes": {"type": "string", "title": "Documentation Modelcard notes", "description": ""}}}, "datasheet": {"type": "object", "properties": {"class": {"type": "string", "title": "Documentation Datasheet Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Documentation Datasheet link", "description": ""}, "notes": {"type": "string", "title": "Documentation Datasheet notes", "description": ""}}}, "package": {"type": "object", "properties": {"class": {"type": "string", "title": "Access Package Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Access Package link", "description": ""}, "notes": {"type": "string", "title": "Access Package notes", "description": ""}}}, "api": {"type": "object", "properties": {"class": {"type": "string", "title": "Access API Class", "description": "Should be closed, open or partial."}, "link": {"type": "string", "format": "uri", "title": "Access API link", "description": ""}, "notes": {"type": "string", "title": "Access API notes", "description": ""}}}}, "$schema": "http://json-schema.org/draft-07/schema"}


# record_projects

id: geitje-ultra
git_filename: projects/geitje-ultra.yaml
format: yaml
field_project_name: Geitje Ultra 7B
field_project_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra
field_project_notes: Dutch instruction-tuned model based on Mistral 7B
field_project_llmbase: Mistral 7B
field_project_rlbase: Ultrafeedback Dutch (synthetic)
field_project_license: CC-BY-ND
field_org_name: Bram van Roy
field_org_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra
field_opencode_class: closed
field_opencode_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra#training-procedure
field_llmdata_class: partial
field_llmdata_link: https://huggingface.co/Rijgersberg/GEITje-7B#geitje--trained-further-on-dutch-texts
field_llmweights_class: open
field_llmweights_link: https://github.com/mistralai/mistral-src#download-the-model
field_llmweights_notes: Mistral base model is available for downloading
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch
field_rldata_notes: Ultrafeedback Dutch (synthetic)
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra/tree/main
field_rlweights_notes: Instruction-tuned model made available through HuggingFace
field_license_class: closed
field_license_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra
field_license_notes: Licensed as CC-BY-ND-4.0 on HuggingFace, though no specific license file or statement found
field_code_class: closed
field_code_notes: Only limited code repositories and no clear centralized documentation of code
field_architecture_class: partial
field_architecture_link: https://huggingface.co/BramVanroy/GEITje-7B-ultra
field_preprint_class: partial
data:
{"project": {"name": "Geitje Ultra 7B", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra", "notes": "Dutch instruction-tuned model based on Mistral 7B", "llmbase": "Mistral 7B", "rlbase": "Ultrafeedback Dutch (synthetic)", "license": "CC-BY-ND"}, "org": {"name": "Bram van Roy", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra", "notes": null}, "opencode": {"class": "closed", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra#training-procedure", "notes": "Mistral has limited source code available. No training code for Geitje found apart from the recipe used with the alignment handbook."}, "llmdata": {"class": "partial", "link": "https://huggingface.co/Rijgersberg/GEITje-7B#geitje--trained-further-on-dutch-texts", "notes": "Mistral provides no documentation of any of its pretraining data. Geitje Ultra 7B is based on Geitje 7B, which does disclose that Dutch pretraining data includes Gigacorpus and MADLAD."}, "llmweights": {"class": "open", "link": "https://github.com/mistralai/mistral-src#download-the-model", "notes": "Mistral base model is available for downloading"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch", "notes": "Ultrafeedback Dutch (synthetic)"}, "rlweights": {"class": "open", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra/tree/main", "notes": "Instruction-tuned model made available through HuggingFace"}, "license": {"class": "closed", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra", "notes": "Licensed as CC-BY-ND-4.0 on HuggingFace, though no specific license file or statement found"}, "code": {"class": "closed", "link": null, "notes": "Only limited code repositories and no clear centralized documentation of code"}, "architecture": {"class": "partial", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra", "notes": "Some information on architecture provided in github repo and HF model card. Training was done using alignment handbook."}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2312.12852v1", "notes": "Preprint documents Dutch language resources but architecture and scientific documentation otherwise lacking due to Mistral base"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/BramVanroy/GEITje-7B-ultra", "notes": "Modelcard on HF provides information on fine-tuning but nothing for the Mistral base LLM"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch", "notes": "Datasheet available for DPO and for the Dutch portions of pretraining data, but not for original Mistral pretraining data, hence partial."}, "package": {"class": "closed", "link": null, "notes": "No package available"}, "api": {"class": "partial", "link": null, "notes": "Model available through HuggingFace API"}}

field_opencode_notes:
Mistral has limited source code available. No training code for Geitje found apart from the recipe used with the alignment handbook.

field_llmdata_notes:
Mistral provides no documentation of any of its pretraining data. Geitje Ultra 7B is based on Geitje 7B, which does disclose that Dutch pretraining data includes Gigacorpus and MADLAD.

field_architecture_notes:
Some information on architecture provided in github repo and HF model card. Training was done using alignment handbook.

field_preprint_notes:
Preprint documents Dutch language resources but architecture and scientific documentation otherwise lacking due to Mistral base

field_datasheet_notes:
Datasheet available for DPO and for the Dutch portions of pretraining data, but not for original Mistral pretraining data, hence partial.


id: BELLE
git_filename: projects/BELLE.yaml
format: yaml
field_project_name: BELLE
field_project_link: https://github.com/LianjiaTech/BELLE
field_project_llmbase: LLaMA & BLOOMZ
field_project_rlbase: alpaca, shareGPT, Belle (synthetic)
field_project_license: Apache License 2.0
field_org_name: KE Technologies
field_org_link: http://www.ke.com
field_opencode_class: open
field_opencode_link: https://github.com/LianjiaTech/BELLE
field_opencode_notes: Repository contains a fair bit of code
field_llmdata_class: partial
field_llmweights_class: partial
field_llmweights_notes: LLaMA based but copyright status unclear
field_rldata_class: partial
field_rldata_link: https://github.com/LianjiaTech/BELLE/tree/main/data/1.5M
field_rldata_notes: Synthetic BELLE training data in Chinese released in batches
field_rlweights_class: partial
field_rlweights_link: https://github.com/LianjiaTech/BELLE/tree/main/models
field_rlweights_notes: Some models available, most only as delta weights requiring separate access to LLaMA
field_license_class: closed
field_license_notes: Lowest common denominator is non-OSI approved LLaMA licence agreement
field_code_class: partial
field_code_link: https://github.com/LianjiaTech/BELLE/blob/main/README_en.md
field_code_notes: Quite some documentation on Github, though not all well-organized
field_architecture_class: open
field_architecture_link: https://github.com/LianjiaTech/BELLE/blob/main/README_en.md
field_architecture_notes: Specified in a fair bit of detail on github
field_preprint_class: open
field_preprint_link: https://arxiv.org/abs/2303.14742
data:
{"project": {"name": "BELLE", "link": "https://github.com/LianjiaTech/BELLE", "notes": null, "llmbase": "LLaMA & BLOOMZ", "rlbase": "alpaca, shareGPT, Belle (synthetic)", "license": "Apache License 2.0"}, "org": {"name": "KE Technologies", "link": "http://www.ke.com", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/LianjiaTech/BELLE", "notes": "Repository contains a fair bit of code"}, "llmdata": {"class": "partial", "link": null, "notes": "Open for variants based on BLOOMZ. Closed for variants based on LLaMA, whose pretraining data is nowhere disclosed or documented."}, "llmweights": {"class": "partial", "link": null, "notes": "LLaMA based but copyright status unclear"}, "rldata": {"class": "partial", "link": "https://github.com/LianjiaTech/BELLE/tree/main/data/1.5M", "notes": "Synthetic BELLE training data in Chinese released in batches"}, "rlweights": {"class": "partial", "link": "https://github.com/LianjiaTech/BELLE/tree/main/models", "notes": "Some models available, most only as delta weights requiring separate access to LLaMA"}, "license": {"class": "closed", "link": null, "notes": "Lowest common denominator is non-OSI approved LLaMA licence agreement"}, "code": {"class": "partial", "link": "https://github.com/LianjiaTech/BELLE/blob/main/README_en.md", "notes": "Quite some documentation on Github, though not all well-organized"}, "architecture": {"class": "open", "link": "https://github.com/LianjiaTech/BELLE/blob/main/README_en.md", "notes": "Specified in a fair bit of detail on github"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2303.14742", "notes": null}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card found"}, "datasheet": {"class": "partial", "link": null, "notes": "No data sheet found"}, "package": {"class": "closed", "link": null, "notes": "No dedicated package available"}, "api": {"class": "closed", "link": null, "notes": "No API found"}}

field_llmdata_notes:
Open for variants based on BLOOMZ. Closed for variants based on LLaMA, whose pretraining data is nowhere disclosed or documented.


id: Open-Assistant
git_filename: projects/Open-Assistant.yaml
format: yaml
field_project_name: Open Assistant
field_project_link: https://open-assistant.io/
field_project_llmbase: Pythia 12B
field_project_rlbase: OpenAssistant Conversations
field_project_license: Apache 2.0
field_org_name: LAION-AI
field_org_link: https://open-assistant.io/
field_opencode_class: open
field_opencode_link: https://github.com/LAION-AI/Open-Assistant
field_opencode_notes: Code includes guide for developers
field_llmdata_class: open
field_llmdata_link: https://github.com/LAION-AI/Open-Assistant/tree/main/data/datasets
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/OpenAssistant
field_llmweights_notes: Model weights in several variants downloadable through HuggingFace
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/OpenAssistant/oasst1
field_rlweights_class: closed
field_rlweights_notes: RLHF weights not separately released
field_license_class: open
field_license_link: https://projects.laion.ai/Open-Assistant/docs/faq#what-license-does-open-assistant-use
field_license_notes: Apache 2.0
field_code_class: open
field_code_link: https://projects.laion.ai/Open-Assistant/docs/intro
field_code_notes: Separate website provides entry point to comprehensive documentation
field_architecture_class: open
field_architecture_link: https://github.com/LAION-AI/Open-Assistant/tree/main/model
field_architecture_notes: Instructions to tune the pipeline on training data
field_preprint_class: partial
data:
{"project": {"name": "Open Assistant", "link": "https://open-assistant.io/", "notes": null, "llmbase": "Pythia 12B", "rlbase": "OpenAssistant Conversations", "license": "Apache 2.0"}, "org": {"name": "LAION-AI", "link": "https://open-assistant.io/", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/LAION-AI/Open-Assistant", "notes": "Code includes guide for developers"}, "llmdata": {"class": "open", "link": "https://github.com/LAION-AI/Open-Assistant/tree/main/data/datasets", "notes": "Datasets documented in detail and recipes for cleaning up and downloading provided in code notebooks."}, "llmweights": {"class": "open", "link": "https://huggingface.co/OpenAssistant", "notes": "Model weights in several variants downloadable through HuggingFace"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/OpenAssistant/oasst1", "notes": "OpenAssistant Conversations is 'a human-generated, human-annotated assistant-style conversation corpus consisting of 161443 messages distributed across 66497 conversation trees, in 35 different languages, annotated with 461292 quality ratings' (preprint)"}, "rlweights": {"class": "closed", "link": null, "notes": "RLHF weights not separately released"}, "license": {"class": "open", "link": "https://projects.laion.ai/Open-Assistant/docs/faq#what-license-does-open-assistant-use", "notes": "Apache 2.0"}, "code": {"class": "open", "link": "https://projects.laion.ai/Open-Assistant/docs/intro", "notes": "Separate website provides entry point to comprehensive documentation"}, "architecture": {"class": "open", "link": "https://github.com/LAION-AI/Open-Assistant/tree/main/model", "notes": "Instructions to tune the pipeline on training data"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs//2304.07327", "notes": "Preprint describes creation of OpenAssistant Conversations corpus for instruction tuning, but not the base LLM, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper or published data audit found"}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "open", "link": null, "notes": null}, "api": {"class": "open", "link": "https://projects.laion.ai/Open-Assistant/api", "notes": null}}

field_llmdata_notes:
Datasets documented in detail and recipes for cleaning up and downloading provided in code notebooks.

field_rldata_notes:
OpenAssistant Conversations is 'a human-generated, human-annotated assistant-style conversation corpus consisting of 161443 messages distributed across 66497 conversation trees, in 35 different languages, annotated with 461292 quality ratings' (preprint)

field_preprint_notes:
Preprint describes creation of OpenAssistant Conversations corpus for instruction tuning, but not the base LLM, hence partial.


id: StableBeluga2
git_filename: projects/StableBeluga2.yaml
format: yaml
field_project_name: Stable Beluga 2
field_project_link: https://huggingface.co/stabilityai/StableBeluga2
field_project_llmbase: LLaMA2
field_project_rlbase: Orca-style (synthetic)
field_project_license: Stable Beluga Non-Commercial Community License
field_org_name: Stability AI
field_org_link: https://stability.ai/
field_opencode_class: closed
field_opencode_notes: No repository with open code related to training, fine-tuning or evaluation found
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/stabilityai/StableBeluga2/tree/main
field_rlweights_notes: Instruction-tuned model weights available
field_license_class: partial
field_license_link: https://huggingface.co/stabilityai/StableBeluga2/blob/main/LICENSE.txt
field_code_class: closed
field_code_notes: Code on HuggingFace only covers minimal examples; no documentation available.
field_architecture_class: partial
field_architecture_link: https://huggingface.co/stabilityai/StableBeluga2#model-details
field_architecture_notes: Says 'Stable Beluga 2 is a Llama2 70B model finetuned on an Orca style Dataset'.
field_preprint_class: partial
field_preprint_link: https://huggingface.co/papers/2306.02707
field_paper_class: closed
field_paper_notes: No peer-reviewed paper found
field_modelcard_class: partial
data:
{"project": {"name": "Stable Beluga 2", "link": "https://huggingface.co/stabilityai/StableBeluga2", "notes": null, "llmbase": "LLaMA2", "rlbase": "Orca-style (synthetic)", "license": "Stable Beluga Non-Commercial Community License"}, "org": {"name": "Stability AI", "link": "https://stability.ai/", "notes": null}, "opencode": {"class": "closed", "link": null, "notes": "No repository with open code related to training, fine-tuning or evaluation found"}, "llmdata": {"class": "closed", "link": null, "notes": "Pretraining data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "Says: 'Stable Beluga 2 is trained on our internal Orca-style dataset', 'created synthetically using high-quality instructions' from COT Submix Original, NIV2 Submix Original, FLAN 2021 Submix Original, T0 Submix Original."}, "rlweights": {"class": "open", "link": "https://huggingface.co/stabilityai/StableBeluga2/tree/main", "notes": "Instruction-tuned model weights available"}, "license": {"class": "partial", "link": "https://huggingface.co/stabilityai/StableBeluga2/blob/main/LICENSE.txt", "notes": "Usage requires signing StabilityAI's bespoke 'Stable Beluga Non-Commercial Community License', not an OSI recognised open license"}, "code": {"class": "closed", "link": null, "notes": "Code on HuggingFace only covers minimal examples; no documentation available."}, "architecture": {"class": "partial", "link": "https://huggingface.co/stabilityai/StableBeluga2#model-details", "notes": "Says 'Stable Beluga 2 is a Llama2 70B model finetuned on an Orca style Dataset'."}, "preprint": {"class": "partial", "link": "https://huggingface.co/papers/2306.02707", "notes": "Preprint from Microsoft describes Orca method of finetuning using GPT4-derived synthetic data, but no details of this particular architecture"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/stabilityai/StableBeluga2", "notes": "There is a model card, but it provides only a minimum of detail"}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "model too large to run on HuggingFace free inference API"}}

field_llmdata_notes:
Pretraining data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_rldata_notes:
Says: 'Stable Beluga 2 is trained on our internal Orca-style dataset', 'created synthetically using high-quality instructions' from COT Submix Original, NIV2 Submix Original, FLAN 2021 Submix Original, T0 Submix Original.

field_license_notes:
Usage requires signing StabilityAI's bespoke 'Stable Beluga Non-Commercial Community License', not an OSI recognised open license

field_preprint_notes:
Preprint from Microsoft describes Orca method of finetuning using GPT4-derived synthetic data, but no details of this particular architecture


id: ChatRWKV
git_filename: projects/ChatRWKV.yaml
format: yaml
field_project_name: ChatRWKV
field_project_link: https://github.com/BlinkDL/ChatRWKV
field_project_llmbase: RWKV-LM
field_project_rlbase: alpaca, shareGPT (synthetic)
field_org_name: BlinkDL/RWKV
field_org_link: https://www.rwkv.com/
field_opencode_class: open
field_opencode_link: https://github.com/BlinkDL/ChatRWKV
field_opencode_notes: Various community-contributed enhancements available
field_llmdata_class: partial
field_llmdata_link: https://pile.eleuther.ai/
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/BlinkDL/rwkv-4-world/tree/main
field_llmweights_notes: Model weights released across different HuggingFace spaces
field_rldata_class: closed
field_rlweights_class: closed
field_rlweights_notes: Weights not separately available.
field_license_class: open
field_license_link: https://github.com/BlinkDL/ChatRWKV/blob/main/LICENSE
field_license_notes: Apache 2.0
field_code_class: partial
field_code_notes: Code documentation scattered across github repo and HuggingFace spaces
field_architecture_class: partial
field_architecture_notes: Architecture described in preprint (LM part) but not all details clearly documented.
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2305.13048
field_preprint_notes: Preprint covers only LLM (RNN based), not instruction fine-tuning, so partial.
field_paper_class: closed
field_paper_notes: No peer-reviewed paper or published data audit known
data:
{"project": {"name": "ChatRWKV", "link": "https://github.com/BlinkDL/ChatRWKV", "notes": null, "llmbase": "RWKV-LM", "rlbase": "alpaca, shareGPT (synthetic)", "license": null}, "org": {"name": "BlinkDL/RWKV", "link": "https://www.rwkv.com/", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/BlinkDL/ChatRWKV", "notes": "Various community-contributed enhancements available"}, "llmdata": {"class": "partial", "link": "https://pile.eleuther.ai/", "notes": "Trained on The Pile. Recent versions also build on Red Pajama (https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T)"}, "llmweights": {"class": "open", "link": "https://huggingface.co/BlinkDL/rwkv-4-world/tree/main", "notes": "Model weights released across different HuggingFace spaces"}, "rldata": {"class": "closed", "link": null, "notes": "Instruction tuning data not separately available. Documentation 'These are RWKV-4-Pile 1.5/3/7/14B models finetuned on Alpaca, CodeAlpaca, Guanaco, GPT4All, ShareGPT and more'"}, "rlweights": {"class": "closed", "link": null, "notes": "Weights not separately available."}, "license": {"class": "open", "link": "https://github.com/BlinkDL/ChatRWKV/blob/main/LICENSE", "notes": "Apache 2.0"}, "code": {"class": "partial", "link": null, "notes": "Code documentation scattered across github repo and HuggingFace spaces"}, "architecture": {"class": "partial", "link": null, "notes": "Architecture described in preprint (LM part) but not all details clearly documented."}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2305.13048", "notes": "Preprint covers only LLM (RNN based), not instruction fine-tuning, so partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper or published data audit known"}, "modelcard": {"class": "closed", "link": "https://huggingface.co/BlinkDL/rwkv-4-raven", "notes": "No modelcard, HuggingFace spaces only used to share files"}, "datasheet": {"class": "closed", "link": "https://huggingface.co/BlinkDL/rwkv-4-raven", "notes": "No data sheet, HuggingFac spaces only used to share files"}, "package": {"class": "open", "link": "https://pypi.org/project/rwkv/", "notes": "Available through pip install rwkv"}, "api": {"class": "partial", "link": null, "notes": "API via HuggingFace"}}

field_llmdata_notes:
Trained on The Pile. Recent versions also build on Red Pajama (https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T)

field_rldata_notes:
Instruction tuning data not separately available. Documentation 'These are RWKV-4-Pile 1.5/3/7/14B models finetuned on Alpaca, CodeAlpaca, Guanaco, GPT4All, ShareGPT and more'


id: chatgpt
git_filename: projects/chatgpt.yaml
format: yaml
field_project_name: ChatGPT
field_project_link: https://chat.openai.com/
field_project_notes: NA
field_project_llmbase: GPT 3.5
field_project_rlbase: Instruct-GPT
field_project_license: NA
field_org_name: OpenAI
field_org_link: https://openai.com/
field_org_notes: NA
field_opencode_class: closed
field_opencode_link: https://chat.openai.com/
field_opencode_notes: OpenAI has not released any source code related to ChatGPT
field_llmdata_class: closed
field_llmdata_notes: OpenAI has not released or documented any of the source training data
field_llmweights_class: closed
field_llmweights_notes: OpenAI has not released model weights for GPT3.5
field_rldata_class: closed
field_rldata_notes: OpenAI has not released the instruction-tuning data
field_rlweights_class: closed
field_rlweights_notes: OpenAI has not released details about RLHF models weights
field_license_class: closed
field_license_notes: None of the code is open sourced; license unknown.
field_code_class: closed
field_code_notes: Code is not available, documentation level unknown.
field_architecture_class: closed
field_architecture_notes: OpenAI has not clearly documented the LLM+RLHF architecture or its evaluation.
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2203.02155
field_preprint_notes: Preprint describes only the instruction-tuning method; no further papers available.
data:
{"project": {"name": "ChatGPT", "link": "https://chat.openai.com/", "notes": "NA", "llmbase": "GPT 3.5", "rlbase": "Instruct-GPT", "license": "NA"}, "org": {"name": "OpenAI", "link": "https://openai.com/", "notes": "NA"}, "opencode": {"class": "closed", "link": "https://chat.openai.com/", "notes": "OpenAI has not released any source code related to ChatGPT"}, "llmdata": {"class": "closed", "link": null, "notes": "OpenAI has not released or documented any of the source training data"}, "llmweights": {"class": "closed", "link": null, "notes": "OpenAI has not released model weights for GPT3.5"}, "rldata": {"class": "closed", "link": null, "notes": "OpenAI has not released the instruction-tuning data"}, "rlweights": {"class": "closed", "link": null, "notes": "OpenAI has not released details about RLHF models weights"}, "license": {"class": "closed", "link": null, "notes": "None of the code is open sourced; license unknown."}, "code": {"class": "closed", "link": null, "notes": "Code is not available, documentation level unknown."}, "architecture": {"class": "closed", "link": null, "notes": "OpenAI has not clearly documented the LLM+RLHF architecture or its evaluation."}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2203.02155", "notes": "Preprint describes only the instruction-tuning method; no further papers available."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper documenting this system is available."}, "modelcard": {"class": "closed", "link": "https://github.com/openai/gpt-3/blob/master/model-card.md", "notes": "No modelcard is available for GPT3.5. The linked model card is for GPT3 is dated Sept 2020."}, "datasheet": {"class": "closed", "link": null, "notes": "OpenAI has not released a datasheet or any other documentation or evaluation of source data."}, "package": {"class": "closed", "link": null, "notes": "Some third party packages exist; support for them is contingent on OpenAI's whims."}, "api": {"class": "closed", "link": null, "notes": "API access is only available for commercial users."}}


id: phi-3-instruct
git_filename: projects/phi-3-instruct.yaml
format: yaml
field_project_name: Phi 3 Instruct
field_project_link: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct
field_project_llmbase: Phi3
field_project_rlbase: Unspecified
field_project_license: MIT License
field_org_name: Microsoft
field_org_link: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct
field_opencode_class: closed
field_opencode_notes: No source code found for pretraining, posttraining, or evaluation
field_llmdata_class: closed
field_llmweights_class: closed
field_llmweights_notes: No base model of the instruction-tuned Phi-3 was released
field_rldata_class: closed
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/tree/main
field_rlweights_notes: Instruction-tuned model weights shared through HuggingFace
field_license_class: open
field_license_link: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/blob/main/LICENSE
field_license_notes: MIT License
field_code_class: closed
field_code_notes: No source code, so no documentation of source code found
field_architecture_class: open
field_architecture_link: https://arxiv.org/abs/2404.14219
field_architecture_notes: Architecture described in model card and preprint
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2404.14219
field_paper_class: closed
field_paper_notes: No paper found
field_modelcard_class: open
data:
{"project": {"name": "Phi 3 Instruct", "link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct", "notes": null, "llmbase": "Phi3", "rlbase": "Unspecified", "license": "MIT License"}, "org": {"name": "Microsoft", "link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct", "notes": null}, "opencode": {"class": "closed", "link": null, "notes": "No source code found for pretraining, posttraining, or evaluation"}, "llmdata": {"class": "closed", "link": null, "notes": "No datasets made available and no information on datasets disclosed except very generic claims about filtering for high quality."}, "llmweights": {"class": "closed", "link": null, "notes": "No base model of the instruction-tuned Phi-3 was released"}, "rldata": {"class": "closed", "link": null, "notes": "No post-training datasets made available and no information on datasets disclosed except very generic claims about filtering for high quality."}, "rlweights": {"class": "open", "link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/tree/main", "notes": "Instruction-tuned model weights shared through HuggingFace"}, "license": {"class": "open", "link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/blob/main/LICENSE", "notes": "MIT License"}, "code": {"class": "closed", "link": null, "notes": "No source code, so no documentation of source code found"}, "architecture": {"class": "open", "link": "https://arxiv.org/abs/2404.14219", "notes": "Architecture described in model card and preprint"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2404.14219", "notes": "Preprint describes model architecture but not training data, focusing mostly on benchmarks and evalution"}, "paper": {"class": "closed", "link": null, "notes": "No paper found"}, "modelcard": {"class": "open", "link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/blob/main/LICENSE", "notes": "Model card provides reasonable level of detail"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet made available"}, "package": {"class": "partial", "link": null, "notes": "Available through development version of transformers"}, "api": {"class": "open", "link": null, "notes": "Available through HuggingFace API"}}

field_llmdata_notes:
No datasets made available and no information on datasets disclosed except very generic claims about filtering for high quality.

field_rldata_notes:
No post-training datasets made available and no information on datasets disclosed except very generic claims about filtering for high quality.

field_preprint_notes:
Preprint describes model architecture but not training data, focusing mostly on benchmarks and evalution


id: Falcon-180B-chat
git_filename: projects/Falcon-180B-chat.yaml
format: yaml
field_project_name: Falcon-180B-chat
field_project_link: https://huggingface.co/tiiuae/falcon-180B-chat
field_project_llmbase: Falcon 180B
field_project_rlbase: OpenPlatypus, Ultrachat, Airoboros (synthetic)
field_project_license: FALCON 180B TII LICENSE VERSION 1.0
field_org_name: Technology Innovation Institute
field_org_link: https://falconllm.tii.ae
field_opencode_class: closed
field_opencode_link: https://huggingface.co/tiiuae/falcon-180B-chat
field_llmdata_class: partial
field_llmdata_link: https://huggingface.co/datasets/tiiuae/falcon-refinedweb
field_llmweights_class: partial
field_llmweights_link: https://huggingface.co/tiiuae/falcon-180B
field_llmweights_notes: requires signing up and accepting "acceptable use policy"
field_rldata_class: partial
field_rldata_link: https://github.com/project-baize/baize-chatbot
field_rldata_notes: No details provided beyond "finetuned on a mixture of Ultrachat, Platypus and Airoboros".
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/tiiuae/falcon-180B-chat/tree/main
field_license_class: closed
field_license_link: https://huggingface.co/spaces/tiiuae/falcon-180b-license/blob/main/LICENSE.txt
field_license_notes: Released under Falcon 180B TII license (not OSI approved) and a separate "acceptable use policy".
field_code_class: closed
field_code_notes: No code available, so no code documented.
field_architecture_class: partial
field_architecture_link: https://huggingface.co/tiiuae/falcon-180B-chat#model-architecture-and-objective
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2306.01116
field_paper_class: closed
data:
{"project": {"name": "Falcon-180B-chat", "link": "https://huggingface.co/tiiuae/falcon-180B-chat", "notes": "Falcon-180B-Chat is a 180B parameters causal decoder-only model built by TII based on Falcon-180B and finetuned on a mixture of Ultrachat, Platypus and Airoboros.", "llmbase": "Falcon 180B", "rlbase": "OpenPlatypus, Ultrachat, Airoboros (synthetic)", "license": "FALCON 180B TII LICENSE VERSION 1.0"}, "org": {"name": "Technology Innovation Institute", "link": "https://falconllm.tii.ae", "notes": null}, "opencode": {"class": "closed", "link": "https://huggingface.co/tiiuae/falcon-180B-chat", "notes": "No source code shared anywhere. The over 200 github repositories of TII appear to include no LLM or Falcon related code."}, "llmdata": {"class": "partial", "link": "https://huggingface.co/datasets/tiiuae/falcon-refinedweb", "notes": "From the documentation 'The key ingredient for the high quality of the Falcon models is their training data, predominantly based (>80%) on RefinedWeb \u2014 a novel massive web dataset based on CommonCrawl' (https://huggingface.co/blog/falcon). However, only a small sample is made available."}, "llmweights": {"class": "partial", "link": "https://huggingface.co/tiiuae/falcon-180B", "notes": "requires signing up and accepting \"acceptable use policy\""}, "rldata": {"class": "partial", "link": "https://github.com/project-baize/baize-chatbot", "notes": "No details provided beyond \"finetuned on a mixture of Ultrachat, Platypus and Airoboros\"."}, "rlweights": {"class": "partial", "link": "https://huggingface.co/tiiuae/falcon-180B-chat/tree/main", "notes": "No RL weights or checkpoints made available; fine-tuned 'chat' model only available after signing \"acceptable use policy\"."}, "license": {"class": "closed", "link": "https://huggingface.co/spaces/tiiuae/falcon-180b-license/blob/main/LICENSE.txt", "notes": "Released under Falcon 180B TII license (not OSI approved) and a separate \"acceptable use policy\"."}, "code": {"class": "closed", "link": null, "notes": "No code available, so no code documented."}, "architecture": {"class": "partial", "link": "https://huggingface.co/tiiuae/falcon-180B-chat#model-architecture-and-objective", "notes": "Architecture described as  \"causal decoder-only\" and \"optimized for inference\", but very few details available."}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2306.01116", "notes": "Preprint covers the creation and curation of RefinedWeb dataset, but not other aspects of the model, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper known."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/tiiuae/falcon-180B-chat", "notes": "Model card on HuggingFace is mostly used to advertise the model, not to document its training and evaluation details."}, "datasheet": {"class": "closed", "link": null, "notes": "There is no datasheet available."}, "package": {"class": "closed", "link": null, "notes": "There is no package."}, "api": {"class": "closed", "link": "https://huggingface.co/tiiuae/falcon-180B-chat", "notes": "There is no API, and HuggingFace inference API is disabled for this model."}}

field_project_notes:
Falcon-180B-Chat is a 180B parameters causal decoder-only model built by TII based on Falcon-180B and finetuned on a mixture of Ultrachat, Platypus and Airoboros.

field_opencode_notes:
No source code shared anywhere. The over 200 github repositories of TII appear to include no LLM or Falcon related code.

field_llmdata_notes:
From the documentation 'The key ingredient for the high quality of the Falcon models is their training data, predominantly based (>80%) on RefinedWeb — a novel massive web dataset based on CommonCrawl' (https://huggingface.co/blog/falcon). However, only a small sample is made available.

field_rlweights_notes:
No RL weights or checkpoints made available; fine-tuned 'chat' model only available after signing "acceptable use policy".

field_architecture_notes:
Architecture described as  "causal decoder-only" and "optimized for inference", but very few details available.

field_preprint_notes:
Preprint covers the creation and curation of RefinedWeb dataset, but not other aspects of the model, hence partial.

field_modelcard_notes:
Model card on HuggingFace is mostly used to advertise the model, not to document its training and evaluation details.


id: nanbeige-chat
git_filename: projects/nanbeige-chat.yaml
format: yaml
field_project_name: Nanbeige2-Chat
field_project_link: https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat
field_project_notes: Comes in 8B and 16B versions
field_project_llmbase: Unknown
field_project_rlbase: Unknown
field_project_license: Apache 2.0 and bespoke community license
field_org_name: Nanbeige LLM lab
field_org_link: https://huggingface.co/Nanbeige
field_opencode_class: open
field_opencode_link: https://github.com/Nanbeige/Nanbeige
field_opencode_notes: github repo contains sparse but clear code for training, tuning, and inference
field_llmdata_class: closed
field_llmweights_class: closed
field_llmweights_notes: Base model not shared
field_rldata_class: closed
field_rldata_link: https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/discussions/2#6621e15a4d17641cf788cbd5
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/tree/main
field_rlweights_notes: Model weights for finetuned model shared
field_license_class: partial
field_license_notes: Apache 2.0 but commercial use requires signup and an additional community license
field_code_class: closed
field_code_notes: No documentation of the codebase
field_architecture_class: closed
field_architecture_notes: Architecture not clearly specified
field_preprint_class: closed
field_preprint_notes: No preprint found
field_paper_class: closed
field_paper_notes: No paper found
data:
{"project": {"name": "Nanbeige2-Chat", "link": "https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat", "notes": "Comes in 8B and 16B versions", "llmbase": "Unknown", "rlbase": "Unknown", "license": "Apache 2.0 and bespoke community license"}, "org": {"name": "Nanbeige LLM lab", "link": "https://huggingface.co/Nanbeige", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/Nanbeige/Nanbeige", "notes": "github repo contains sparse but clear code for training, tuning, and inference"}, "llmdata": {"class": "closed", "link": null, "notes": "No information on pre-training datasets except a claim of 4.5T tokens. Request for information on HF community was closed without comment."}, "llmweights": {"class": "closed", "link": null, "notes": "Base model not shared"}, "rldata": {"class": "closed", "link": "https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/discussions/2#6621e15a4d17641cf788cbd5", "notes": "No information on finetuning and DPO datasets. Some information provided on request (see link), but official documentation not updated."}, "rlweights": {"class": "open", "link": "https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/tree/main", "notes": "Model weights for finetuned model shared"}, "license": {"class": "partial", "link": null, "notes": "Apache 2.0 but commercial use requires signup and an additional community license"}, "code": {"class": "closed", "link": null, "notes": "No documentation of the codebase"}, "architecture": {"class": "closed", "link": null, "notes": "Architecture not clearly specified"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found"}, "paper": {"class": "closed", "link": null, "notes": "No paper found"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card found"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet found"}, "package": {"class": "closed", "link": null, "notes": "No package found"}, "api": {"class": "partial", "link": "https://huggingface.co/spaces/Nanbeige/Nanbeige-Plus-Chat-v0.1", "notes": "No API, but HuggingFace space available"}}

field_llmdata_notes:
No information on pre-training datasets except a claim of 4.5T tokens. Request for information on HF community was closed without comment.

field_rldata_notes:
No information on finetuning and DPO datasets. Some information provided on request (see link), but official documentation not updated.


id: dolly
git_filename: projects/dolly.yaml
format: yaml
field_project_name: dolly
field_project_link: https://github.com/databrickslabs/dolly
field_project_llmbase: EleutherAI pythia
field_project_rlbase: databricks-dolly-15k
field_org_name: databricks
field_org_link: https://www.databricks.com
field_opencode_class: open
field_llmdata_class: open
field_llmweights_class: open
field_rldata_class: open
field_rlweights_class: closed
field_license_class: open
field_code_class: open
field_architecture_class: open
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2304.01373
field_paper_class: closed
field_modelcard_class: closed
field_datasheet_class: closed
field_package_class: open
field_api_class: closed
data:
{"project": {"name": "dolly", "link": "https://github.com/databrickslabs/dolly", "notes": null, "llmbase": "EleutherAI pythia", "rlbase": "databricks-dolly-15k", "license": null}, "org": {"name": "databricks", "link": "https://www.databricks.com", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "open", "link": null, "notes": null}, "llmweights": {"class": "open", "link": null, "notes": null}, "rldata": {"class": "open", "link": null, "notes": null}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": null}, "code": {"class": "open", "link": null, "notes": null}, "architecture": {"class": "open", "link": null, "notes": null}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2304.01373", "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "open", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}


id: yi-chat
git_filename: projects/yi-chat.yaml
format: yaml
field_project_name: Yi 34B Chat
field_project_link: https://huggingface.co/01-ai/Yi-34B-Chat
field_project_llmbase: Yi 34B
field_project_rlbase: unspecified
field_project_license: Apache 2.0 and bespoke Yi Series Community License Agreement 2.1
field_org_name: 01.AI
field_org_link: https://www.01.ai/
field_opencode_class: partial
field_opencode_link: https://github.com/01-ai/Yi
field_llmdata_class: closed
field_llmdata_notes: Training data for base model undocumented, though preprint mentions CommonCrawl as one source
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/01-ai/Yi-34B/tree/main
field_llmweights_notes: Base model weights shared via HuggingFace
field_rldata_class: closed
field_rldata_link: https://huggingface.co/datasets/BAAI/COIG
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/01-ai/Yi-34B-Chat/tree/main
field_rlweights_notes: Instruction-tuned weights shared via HuggingFace
field_license_class: partial
field_code_class: closed
field_code_link: https://github.com/01-ai/Yi/
field_architecture_class: closed
field_architecture_notes: Model architecture only described in the most general terms.
field_preprint_class: open
field_preprint_link: https://arxiv.org/abs/2403.04652
field_paper_class: closed
field_paper_notes: No paper found
field_modelcard_class: closed
data:
{"project": {"name": "Yi 34B Chat", "link": "https://huggingface.co/01-ai/Yi-34B-Chat", "notes": "The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI. Targeted as a bilingual language model and trained on 3T multilingual corpus.", "llmbase": "Yi 34B", "rlbase": "unspecified", "license": "Apache 2.0 and bespoke Yi Series Community License Agreement 2.1"}, "org": {"name": "01.AI", "link": "https://www.01.ai/", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/01-ai/Yi", "notes": "repository contains some code for demos and for instruction tuning, but only sparse examples of code for initial training and model architecture"}, "llmdata": {"class": "closed", "link": null, "notes": "Training data for base model undocumented, though preprint mentions CommonCrawl as one source"}, "llmweights": {"class": "open", "link": "https://huggingface.co/01-ai/Yi-34B/tree/main", "notes": "Base model weights shared via HuggingFace"}, "rldata": {"class": "closed", "link": "https://huggingface.co/datasets/BAAI/COIG", "notes": "Model docs mention COIG but only as an example. Code also shows rm-static is also used in instruction tuning, but not shared."}, "rlweights": {"class": "open", "link": "https://huggingface.co/01-ai/Yi-34B-Chat/tree/main", "notes": "Instruction-tuned weights shared via HuggingFace"}, "license": {"class": "partial", "link": null, "notes": "Model code licensed under Apache 2.0, model weights licensed under Llama-inspired community license with limitations"}, "code": {"class": "closed", "link": "https://github.com/01-ai/Yi/", "notes": "Documentation only describes how to deploy, training and fine-tuning code not available or where available not commented or documented"}, "architecture": {"class": "closed", "link": null, "notes": "Model architecture only described in the most general terms."}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2403.04652", "notes": "Preprint provides some info on pretraining data (CommonCrawl) but none on instruction tuning dataset."}, "paper": {"class": "closed", "link": null, "notes": "No paper found"}, "modelcard": {"class": "closed", "link": null, "notes": "Model card used for advertising and navigation purposes, does not follow general model card specifications."}, "datasheet": {"class": "closed", "link": null, "notes": "No data sheets found."}, "package": {"class": "closed", "link": null, "notes": "no package found"}, "api": {"class": "partial", "link": null, "notes": "limited access via HF API, otherwise gated and commercially available"}}

field_project_notes:
The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI. Targeted as a bilingual language model and trained on 3T multilingual corpus.

field_opencode_notes:
repository contains some code for demos and for instruction tuning, but only sparse examples of code for initial training and model architecture

field_rldata_notes:
Model docs mention COIG but only as an example. Code also shows rm-static is also used in instruction tuning, but not shared.

field_license_notes:
Model code licensed under Apache 2.0, model weights licensed under Llama-inspired community license with limitations

field_code_notes:
Documentation only describes how to deploy, training and fine-tuning code not available or where available not commented or documented

field_preprint_notes:
Preprint provides some info on pretraining data (CommonCrawl) but none on instruction tuning dataset.

field_modelcard_notes:
Model card used for advertising and navigation purposes, does not follow general model card specifications.


id: gemma-instruct
git_filename: projects/gemma-instruct.yaml
format: yaml
field_project_name: Gemma 7B Instruct
field_project_link: https://ai.google.dev/gemma/docs
field_project_notes: Model weights and developer tools
field_project_llmbase: Gemma
field_project_rlbase: Unspecified
field_org_name: Google DeepMind
field_org_link: https://ai.google.dev/gemma/docs
field_opencode_class: partial
field_opencode_link: https://github.com/google-deepmind/gemma
field_opencode_notes: No pre-training or instructing-tuning code made available. Some developer tools available.
field_llmdata_class: closed
field_llmdata_notes: No details provided on pre-training data.
field_llmweights_class: partial
field_llmweights_link: https://www.kaggle.com/models/keras/gemma/frameworks/keras/variations/gemma_7b_en
field_llmweights_notes: Base model weights shared via Kaggle, requires privacy-defying access request.
field_rldata_class: closed
field_rlweights_class: partial
field_rlweights_notes: Instruction-tuned model weights shared via Kaggle, requires privacy-defying access request
field_license_class: closed
field_license_link: https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/335?pli=1
field_code_class: closed
field_architecture_class: partial
field_architecture_link: https://www.kaggle.com/models/google/gemma
field_architecture_notes: Architecture described in very general terms in model card
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2403.08295
field_paper_class: closed
field_paper_notes: No paper found
field_modelcard_class: open
data:
{"project": {"name": "Gemma 7B Instruct", "link": "https://ai.google.dev/gemma/docs", "notes": "Model weights and developer tools", "llmbase": "Gemma", "rlbase": "Unspecified", "license": null}, "org": {"name": "Google DeepMind", "link": "https://ai.google.dev/gemma/docs", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/google-deepmind/gemma", "notes": "No pre-training or instructing-tuning code made available. Some developer tools available."}, "llmdata": {"class": "closed", "link": null, "notes": "No details provided on pre-training data."}, "llmweights": {"class": "partial", "link": "https://www.kaggle.com/models/keras/gemma/frameworks/keras/variations/gemma_7b_en", "notes": "Base model weights shared via Kaggle, requires privacy-defying access request."}, "rldata": {"class": "closed", "link": null, "notes": "Documentation says 'These versions of the model are trained with human language interactions and can respond to conversational input, similar to a chat bot.' "}, "rlweights": {"class": "partial", "link": null, "notes": "Instruction-tuned model weights shared via Kaggle, requires privacy-defying access request"}, "license": {"class": "closed", "link": "https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/335?pli=1", "notes": "Bespoke Gemma Community License Agreement and restrictive Terms of Use, neither open in the sense of OSI. Only Inference code shared under Apache 2.0."}, "code": {"class": "closed", "link": null, "notes": "No pretraining or finetuning code found. No code documentation except for deployment of the open weights."}, "architecture": {"class": "partial", "link": "https://www.kaggle.com/models/google/gemma", "notes": "Architecture described in very general terms in model card"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2403.08295", "notes": "Preprint released Apr 2024 details architecture and evaluation, but provides no information on pre-training, instruction tuning and SFT datasets"}, "paper": {"class": "closed", "link": null, "notes": "No paper found"}, "modelcard": {"class": "open", "link": "https://www.kaggle.com/models/google/gemma", "notes": "Model card on Kaggle provides some detail on model internals and evaluation"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet found, pre-training and instruction-tuning data nowhere specified."}, "package": {"class": "closed", "link": null, "notes": "No package provided, access is gated through Kaggle, Vertex Model Garden, Google Cloud"}, "api": {"class": "closed", "link": null, "notes": "No API provided, access gated through Kaggle, Vertex Model Garden, Google Cloud"}}

field_rldata_notes:
Documentation says 'These versions of the model are trained with human language interactions and can respond to conversational input, similar to a chat bot.' 

field_license_notes:
Bespoke Gemma Community License Agreement and restrictive Terms of Use, neither open in the sense of OSI. Only Inference code shared under Apache 2.0.

field_code_notes:
No pretraining or finetuning code found. No code documentation except for deployment of the open weights.

field_preprint_notes:
Preprint released Apr 2024 details architecture and evaluation, but provides no information on pre-training, instruction tuning and SFT datasets


id: stablevicuna
git_filename: projects/stablevicuna.yaml
format: yaml
field_project_name: StableVicuna-13B
field_project_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta
field_project_llmbase: LLaMA
field_project_rlbase: OASST1 (human), GPT4All (human), Alpaca (synthetic)
field_org_name: CarperAI
field_org_link: https://carper.ai
field_opencode_class: partial
field_opencode_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta/tree/main
field_opencode_notes: Some elements of the code made available through HuggingFace
field_llmdata_class: closed
field_llmdata_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta
field_llmdata_notes: Based on LLaMA whose pretraining data has nowhere been disclosed or documented.
field_llmweights_class: partial
field_llmweights_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta#apply-delta-weights
field_rldata_class: partial
field_rldata_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta/discussions/7
field_rlweights_notes: The HuggingFace community page has an open question for release of the RL model
field_license_class: partial
field_license_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta
field_code_class: partial
field_code_link: https://huggingface.co/CarperAI/stable-vicuna-13b-delta/tree/main
field_architecture_class: partial
field_architecture_notes: Architecture is described in scattered places, but there is no clear and exhaustive overview.
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2302.13971
field_preprint_notes: Preprint covers only the LLaMA base model, hence partial.
field_paper_class: closed
data:
{"project": {"name": "StableVicuna-13B", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta", "notes": "StableVicuna-13B is a Vicuna-13B v0 model fine-tuned using reinforcement learning from human feedback (RLHF) via Proximal Policy Optimization (PPO) on various conversational and instructional datasets", "llmbase": "LLaMA", "rlbase": "OASST1 (human), GPT4All (human), Alpaca (synthetic)", "license": null}, "org": {"name": "CarperAI", "link": "https://carper.ai", "notes": null}, "opencode": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta/tree/main", "notes": "Some elements of the code made available through HuggingFace"}, "llmdata": {"class": "closed", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta", "notes": "Based on LLaMA whose pretraining data has nowhere been disclosed or documented."}, "llmweights": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta#apply-delta-weights", "notes": "Model not functional out of the box as weights require a delta computation. From the docs 'StableVicuna-13B cannot be used from the CarperAI/stable-vicuna-13b-delta weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and CarperAI/stable-vicuna-13b-delta weights.'"}, "rldata": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta", "notes": "From the documentation 'The reward model used during RLHF was also trained on OpenAssistant Conversations Dataset (OASST1) along with two other datasets Anthropic HH-RLHF, a dataset of preferences about AI assistant helpfulness and harmlessness; and Stanford Human Preferences Dataset a dataset of 385K collective human preferences over responses to questions/instructions in 18 different subject areas, from cooking to legal advice.'"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta/discussions/7", "notes": "The HuggingFace community page has an open question for release of the RL model"}, "license": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta", "notes": "CC-BY-NC-SA-4.0. License for LLaMA is more murky, hence partial. As they say 'License for the base LLaMA model's weights is Meta's non-commercial bespoke license.'"}, "code": {"class": "partial", "link": "https://huggingface.co/CarperAI/stable-vicuna-13b-delta/tree/main", "notes": "Code is minimally documented and deployment requires non-trivial configuration, e.g. 'StableVicuna-13B cannot be used from the CarperAI/stable-vicuna-13b-delta weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and CarperAI/stable-vicuna-13b-delta weights.'"}, "architecture": {"class": "partial", "link": null, "notes": "Architecture is described in scattered places, but there is no clear and exhaustive overview."}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2302.13971", "notes": "Preprint covers only the LLaMA base model, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No paper found."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/lmsys/vicuna-13b-delta-v0", "notes": "Model card provides some information but is not fully worked out as recommended in model card literature."}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet found"}, "package": {"class": "closed", "link": null, "notes": "No package found"}, "api": {"class": "partial", "link": "https://github.com/lm-sys/FastChat/tree/main#api", "notes": "Addressable via FastChat / HuggingFace API"}}

field_project_notes:
StableVicuna-13B is a Vicuna-13B v0 model fine-tuned using reinforcement learning from human feedback (RLHF) via Proximal Policy Optimization (PPO) on various conversational and instructional datasets

field_llmweights_notes:
Model not functional out of the box as weights require a delta computation. From the docs 'StableVicuna-13B cannot be used from the CarperAI/stable-vicuna-13b-delta weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and CarperAI/stable-vicuna-13b-delta weights.'

field_rldata_notes:
From the documentation 'The reward model used during RLHF was also trained on OpenAssistant Conversations Dataset (OASST1) along with two other datasets Anthropic HH-RLHF, a dataset of preferences about AI assistant helpfulness and harmlessness; and Stanford Human Preferences Dataset a dataset of 385K collective human preferences over responses to questions/instructions in 18 different subject areas, from cooking to legal advice.'

field_license_notes:
CC-BY-NC-SA-4.0. License for LLaMA is more murky, hence partial. As they say 'License for the base LLaMA model's weights is Meta's non-commercial bespoke license.'

field_code_notes:
Code is minimally documented and deployment requires non-trivial configuration, e.g. 'StableVicuna-13B cannot be used from the CarperAI/stable-vicuna-13b-delta weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and CarperAI/stable-vicuna-13b-delta weights.'

field_modelcard_notes:
Model card provides some information but is not fully worked out as recommended in model card literature.


id: vicuna13B-lmsys
git_filename: projects/vicuna13B-lmsys.yaml
format: yaml
field_project_name: Vicuna 13B v 1.3
field_project_link: https://huggingface.co/lmsys/vicuna-13b-v1.3
field_project_llmbase: LLaMA
field_project_rlbase: ShareGPT
field_project_license: Non-commercial license
field_org_name: LMSYS
field_org_link: https://lmsys.org/
field_opencode_class: open
field_opencode_link: https://github.com/lm-sys/FastChat
field_opencode_notes: Actively maintained repository
field_llmdata_class: partial
field_llmdata_link: https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md#training-dataset
field_llmweights_class: open
field_llmweights_link: https://github.com/lm-sys/FastChat#vicuna-weights
field_llmweights_notes: Unlike Vicuna 13B v0, these weights do not require applying delta
field_rldata_class: closed
field_rldata_link: https://github.com/lm-sys/FastChat#fine-tuning
field_rlweights_class: closed
field_rlweights_link: https://github.com/lm-sys/FastChat#fine-tuning
field_rlweights_notes: No model weights are shared for the instruction tuning
field_license_class: partial
field_license_link: https://github.com/lm-sys/FastChat#vicuna-weights
field_license_notes: From the documentation 'Vicuna is based on LLaMA and should be used under LLaMA's model license.'
field_code_class: open
field_code_link: https://github.com/lm-sys/FastChat
field_code_notes: Code is quite well-documented and released as part of the FastChat framework.
field_architecture_class: closed
field_preprint_class: open
field_preprint_link: https://arxiv.org/pdf/2306.05685.pdf
data:
{"project": {"name": "Vicuna 13B v 1.3", "link": "https://huggingface.co/lmsys/vicuna-13b-v1.3", "notes": "Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.", "llmbase": "LLaMA", "rlbase": "ShareGPT", "license": "Non-commercial license"}, "org": {"name": "LMSYS", "link": "https://lmsys.org/", "notes": "According to its website, 'The Large Model Systems Organisation develops large models and systems that are open, accessible and scalable'"}, "opencode": {"class": "open", "link": "https://github.com/lm-sys/FastChat", "notes": "Actively maintained repository"}, "llmdata": {"class": "partial", "link": "https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md#training-dataset", "notes": "Vicuna is fine-tuned LLaMA, and LLaMA in turn is based on 'publicly available datasets' that are not all specified or easily downloadable."}, "llmweights": {"class": "open", "link": "https://github.com/lm-sys/FastChat#vicuna-weights", "notes": "Unlike Vicuna 13B v0, these weights do not require applying delta"}, "rldata": {"class": "closed", "link": "https://github.com/lm-sys/FastChat#fine-tuning", "notes": "From the documentation 'We will not release the ShareGPT dataset'. Also 'Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning. The training data is around 140K conversations collected from ShareGPT.com.'"}, "rlweights": {"class": "closed", "link": "https://github.com/lm-sys/FastChat#fine-tuning", "notes": "No model weights are shared for the instruction tuning"}, "license": {"class": "partial", "link": "https://github.com/lm-sys/FastChat#vicuna-weights", "notes": "From the documentation 'Vicuna is based on LLaMA and should be used under LLaMA's model license.'"}, "code": {"class": "open", "link": "https://github.com/lm-sys/FastChat", "notes": "Code is quite well-documented and released as part of the FastChat framework."}, "architecture": {"class": "closed", "link": null, "notes": null}, "preprint": {"class": "open", "link": "https://arxiv.org/pdf/2306.05685.pdf", "notes": "Preprint covers training of the Vicuna model."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/lmsys/vicuna-13b-v1.3", "notes": "Minimal model card, but many details are not provided or have to be pieced together from elsewhere."}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet provided."}, "package": {"class": "open", "link": "https://pypi.org/project/fschat/0.1.2/", "notes": "Available via pip"}, "api": {"class": "partial", "link": "https://github.com/lm-sys/FastChat#api", "notes": "Support provided for several APIs OpenAI restful, HuggingFace, Langchain"}}

field_project_notes:
Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.

field_org_notes:
According to its website, 'The Large Model Systems Organisation develops large models and systems that are open, accessible and scalable'

field_llmdata_notes:
Vicuna is fine-tuned LLaMA, and LLaMA in turn is based on 'publicly available datasets' that are not all specified or easily downloadable.

field_rldata_notes:
From the documentation 'We will not release the ShareGPT dataset'. Also 'Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning. The training data is around 140K conversations collected from ShareGPT.com.'


id: A_sample
git_filename: projects/A_sample.yaml
format: yaml
field_opencode_class: closed
field_llmdata_class: closed
field_llmweights_class: closed
field_rldata_class: closed
field_rlweights_class: closed
field_license_class: closed
field_code_class: closed
field_architecture_class: closed
field_preprint_class: closed
field_paper_class: closed
field_modelcard_class: closed
field_datasheet_class: closed
field_package_class: closed
field_api_class: closed
data:
{"project": {"name": null, "link": null, "notes": null, "llmbase": null, "rlbase": null, "license": null}, "org": {"name": null, "link": null, "notes": null}, "opencode": {"class": "closed", "link": null, "notes": null}, "llmdata": {"class": "closed", "link": null, "notes": null}, "llmweights": {"class": "closed", "link": null, "notes": null}, "rldata": {"class": "closed", "link": null, "notes": null}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "closed", "link": null, "notes": null}, "code": {"class": "closed", "link": null, "notes": null}, "architecture": {"class": "closed", "link": null, "notes": null}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "closed", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}


id: tulu-2-70b
git_filename: projects/tulu-2-70b.yaml
format: yaml
field_project_name: Tulu V2 DPO 70B
field_project_link: https://huggingface.co/allenai/tulu-2-dpo-70b
field_project_notes: A new DPO model from AllenAI called Tülu
field_project_llmbase: Llama2
field_project_rlbase: Tulu SFT, Ultrafeedback
field_project_license: AI2 ImpACT license
field_org_name: AllenAI
field_org_link: https://allenai.org/
field_opencode_class: open
field_opencode_link: https://github.com/allenai/open-instruct
field_llmdata_class: closed
field_llmdata_notes: Based on Llama2 so nothing known about training data
field_llmweights_class: partial
field_llmweights_link: https://github.com/meta-llama/
field_llmweights_notes: Base model made available via Meta (requires privacy-defying signup)
field_rldata_class: open
field_rldata_link: https://github.com/allenai/open-instruct
field_rldata_notes: Codebase used for fine-tuning this model and made available for others
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/allenai/tulu-2-dpo-70b/tree/main
field_rlweights_notes: Fine-tuned weights available
field_license_class: partial
field_license_link: https://allenai.org/impact-license
field_license_notes: Meta Community License and AI2 Impact license
field_code_class: partial
field_code_link: https://github.com/allenai/open-instruct
field_code_notes: OpenInstruct code well-documented
field_architecture_class: partial
field_architecture_link: https://huggingface.co/HuggingFaceH4/zephyr-7b-beta
data:
{"project": {"name": "Tulu V2 DPO 70B", "link": "https://huggingface.co/allenai/tulu-2-dpo-70b", "notes": "A new DPO model from AllenAI called T\u00fclu", "llmbase": "Llama2", "rlbase": "Tulu SFT, Ultrafeedback", "license": "AI2 ImpACT license"}, "org": {"name": "AllenAI", "link": "https://allenai.org/", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/allenai/open-instruct", "notes": "Important effort to make available fine-tuning procedure and source code. Not seen a repository for base model training yet."}, "llmdata": {"class": "closed", "link": null, "notes": "Based on Llama2 so nothing known about training data"}, "llmweights": {"class": "partial", "link": "https://github.com/meta-llama/", "notes": "Base model made available via Meta (requires privacy-defying signup)"}, "rldata": {"class": "open", "link": "https://github.com/allenai/open-instruct", "notes": "Codebase used for fine-tuning this model and made available for others"}, "rlweights": {"class": "open", "link": "https://huggingface.co/allenai/tulu-2-dpo-70b/tree/main", "notes": "Fine-tuned weights available"}, "license": {"class": "partial", "link": "https://allenai.org/impact-license", "notes": "Meta Community License and AI2 Impact license"}, "code": {"class": "partial", "link": "https://github.com/allenai/open-instruct", "notes": "OpenInstruct code well-documented"}, "architecture": {"class": "partial", "link": "https://huggingface.co/HuggingFaceH4/zephyr-7b-beta", "notes": "Post-llama2 aspects quite well described in papers, e.g. DPO based on Zephyr Beta, but base model is irrevocably closed"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2311.10702", "notes": "Preprint covers the training of Tulu2"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed work found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/allenai/tulu-2-70b", "notes": "Model card offers little details"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture", "notes": "Some datasheets available (for instruction tuning), but base model entirely undocumented."}, "package": {"class": "closed", "link": null, "notes": "No separate package found"}, "api": {"class": "open", "link": null, "notes": "Available via various APIs"}}

field_opencode_notes:
Important effort to make available fine-tuning procedure and source code. Not seen a repository for base model training yet.

field_architecture_notes:
Post-llama2 aspects quite well described in papers, e.g. DPO based on Zephyr Beta, but base model is irrevocably closed


id: wizardlm-13B
git_filename: projects/wizardlm-13B.yaml
format: yaml
field_project_name: WizardLM 13B v1.2
field_project_link: https://huggingface.co/WizardLM/WizardLM-13B-V1.2
field_project_notes: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
field_project_llmbase: LLaMA2-13B
field_project_rlbase: Evol-Instruct (synthetic)
field_project_license: CC-BY-NC-4.0
field_org_name: Microsoft & Peking University
field_org_link: https://github.com/nlpxucan
field_opencode_class: partial
field_opencode_link: https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
field_opencode_notes: Fast-evolving repository contains WizardLM code
field_llmdata_class: closed
field_llmdata_notes: Based on LLaMA2, which is claimed to be public but nowhere exactly documented.
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Based on LLaMA2 weights, which are made conditionally available by Meta.
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/WizardLM/WizardLM-13B-V1.2
field_rlweights_notes: Model weights offered in HuggingFace repository
field_license_class: partial
field_license_link: https://github.com/nlpxucan/WizardLM/blob/main/WizardLM/MODEL_DIFF_LICENSE
field_code_class: partial
field_code_link: https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
field_code_notes: Code is only partially documented, not clearly versioned, and appears to be in flux.
field_architecture_class: open
field_architecture_link: https://arxiv.org/abs/2304.12244
field_architecture_notes: Architecture described in preprint and partly accessible in code repository
data:
{"project": {"name": "WizardLM 13B v1.2", "link": "https://huggingface.co/WizardLM/WizardLM-13B-V1.2", "notes": "Empowering Large Pre-Trained Language Models to Follow Complex Instructions", "llmbase": "LLaMA2-13B", "rlbase": "Evol-Instruct (synthetic)", "license": "CC-BY-NC-4.0"}, "org": {"name": "Microsoft & Peking University", "link": "https://github.com/nlpxucan", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/tree/main/WizardLM", "notes": "Fast-evolving repository contains WizardLM code"}, "llmdata": {"class": "closed", "link": "https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io/blob/main/projects/llama-2-chat.yaml", "notes": "Based on LLaMA2, which is claimed to be public but nowhere exactly documented."}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Based on LLaMA2 weights, which are made conditionally available by Meta."}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k", "notes": "The Evol-Instruct V2 dataset contains 196k instruction-following sequences generated from Evol-Instruct"}, "rlweights": {"class": "open", "link": "https://huggingface.co/WizardLM/WizardLM-13B-V1.2", "notes": "Model weights offered in HuggingFace repository"}, "license": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/blob/main/WizardLM/MODEL_DIFF_LICENSE", "notes": "Restricted for academic research purposes only. Code and Model diff release under CC-BY-NC-4.0, software code under Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/tree/main/WizardLM", "notes": "Code is only partially documented, not clearly versioned, and appears to be in flux."}, "architecture": {"class": "open", "link": "https://arxiv.org/abs/2304.12244", "notes": "Architecture described in preprint and partly accessible in code repository"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2304.12244", "notes": "Preprint describes method for creating large amounts of LLM-based synthetic RLHF data and fine-tuning WizardLM based on it"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper or data audit found"}, "modelcard": {"class": "closed", "link": "https://huggingface.co/WizardLM/WizardLM-13B-V1.2", "notes": "Model card is only a placeholder and generates an error (missing yaml metadata)"}, "datasheet": {"class": "closed", "link": "https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k", "notes": "Dataset card for Evol-Instruct generates an error"}, "package": {"class": "closed", "link": null, "notes": "No package available"}, "api": {"class": "closed", "link": null, "notes": "No API available"}}

field_llmdata_link:
https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io/blob/main/projects/llama-2-chat.yaml

field_rldata_notes:
The Evol-Instruct V2 dataset contains 196k instruction-following sequences generated from Evol-Instruct

field_license_notes:
Restricted for academic research purposes only. Code and Model diff release under CC-BY-NC-4.0, software code under Apache 2.0

field_preprint_notes:
Preprint describes method for creating large amounts of LLM-based synthetic RLHF data and fine-tuning WizardLM based on it


id: koala
git_filename: projects/koala.yaml
format: yaml
field_project_name: Koala 13B
field_project_link: https://bair.berkeley.edu/blog/2023/04/03/koala/
field_project_llmbase: LLaMA 13B
field_project_rlbase: HC3, ShareGPT, alpaca (synthetic)
field_project_license: Mixed
field_org_name: BAIR
field_org_link: https://bair.berkeley.edu/
field_org_notes: Berkeley Artificial Intelligence Research
field_opencode_class: open
field_opencode_link: https://github.com/young-geng/EasyLM
field_opencode_notes: Code scattered across projects and repositories
field_llmdata_class: partial
field_llmdata_link: https://github.com/young-geng/koala_data_pipeline
field_llmweights_class: partial
field_llmweights_link: https://drive.google.com/drive/folders/10f7wrlAFoPIy-TECHsx9DKIvbQYunCfl
field_rldata_class: partial
field_rldata_link: https://bair.berkeley.edu/blog/2023/04/03/koala/#datasets-and-training
field_rldata_notes: Datasets described in blog post but not all made available
field_rlweights_class: closed
field_rlweights_notes: RL weights not made available separately
field_license_class: partial
field_license_link: https://huggingface.co/young-geng/koala#license
field_code_class: partial
field_code_link: https://github.com/young-geng/EasyLM
field_code_notes: Code scattered across various repositories and not systematically documented.
field_architecture_class: partial
field_architecture_link: https://github.com/young-geng/EasyLM
field_architecture_notes: Architecture visually illustrated and described in some detail.
field_preprint_class: closed
data:
{"project": {"name": "Koala 13B", "link": "https://bair.berkeley.edu/blog/2023/04/03/koala/", "notes": "From the documentation 'Koala is fine-tuned on freely available interaction data scraped from the web, but with a specific focus on data that includes interaction with highly capable closed-source models such as ChatGPT.'", "llmbase": "LLaMA 13B", "rlbase": "HC3, ShareGPT, alpaca (synthetic)", "license": "Mixed"}, "org": {"name": "BAIR", "link": "https://bair.berkeley.edu/", "notes": "Berkeley Artificial Intelligence Research"}, "opencode": {"class": "open", "link": "https://github.com/young-geng/EasyLM", "notes": "Code scattered across projects and repositories"}, "llmdata": {"class": "partial", "link": "https://github.com/young-geng/koala_data_pipeline", "notes": "Repo contains data pipeline for preprocessing. Based on LLaMA which is said to be based on 'publicly available datasets' which are not made directly available."}, "llmweights": {"class": "partial", "link": "https://drive.google.com/drive/folders/10f7wrlAFoPIy-TECHsx9DKIvbQYunCfl", "notes": "Model weights only made available as a diff against LLaMA. OpenLLaMA provides a possible alternative?"}, "rldata": {"class": "partial", "link": "https://bair.berkeley.edu/blog/2023/04/03/koala/#datasets-and-training", "notes": "Datasets described in blog post but not all made available"}, "rlweights": {"class": "closed", "link": null, "notes": "RL weights not made available separately"}, "license": {"class": "partial", "link": "https://huggingface.co/young-geng/koala#license", "notes": "Licensing is 'subject to the model License of LLaMA, Terms of Use of the data generated by OpenAI, and Privacy Practices of ShareGPT'"}, "code": {"class": "partial", "link": "https://github.com/young-geng/EasyLM", "notes": "Code scattered across various repositories and not systematically documented."}, "architecture": {"class": "partial", "link": "https://github.com/young-geng/EasyLM", "notes": "Architecture visually illustrated and described in some detail."}, "preprint": {"class": "closed", "link": null, "notes": "No preprint available"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card available"}, "datasheet": {"class": "closed", "link": null, "notes": "No systematic data sheet available"}, "package": {"class": "closed", "link": null, "notes": "No package available"}, "api": {"class": "closed", "link": null, "notes": "No API available"}}

field_project_notes:
From the documentation 'Koala is fine-tuned on freely available interaction data scraped from the web, but with a specific focus on data that includes interaction with highly capable closed-source models such as ChatGPT.'

field_llmdata_notes:
Repo contains data pipeline for preprocessing. Based on LLaMA which is said to be based on 'publicly available datasets' which are not made directly available.

field_llmweights_notes:
Model weights only made available as a diff against LLaMA. OpenLLaMA provides a possible alternative?

field_license_notes:
Licensing is 'subject to the model License of LLaMA, Terms of Use of the data generated by OpenAI, and Privacy Practices of ShareGPT'


id: mixtral-8x7B-instruct
git_filename: projects/mixtral-8x7B-instruct.yaml
format: yaml
field_project_name: Mixtral 8x7B Instruct
field_project_link: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
field_project_llmbase: Mistral
field_project_rlbase: Unspecified
field_project_license: Apache 2.0
field_org_name: Mistral AI
field_org_link: https://mistral.ai
field_opencode_class: closed
field_opencode_notes: No training code for Mixtral 8x7B made available
field_llmdata_class: closed
field_llmdata_notes: No information provided on pretraining data
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/mistralai/Mixtral-8x7B-v0.1/tree/main
field_llmweights_notes: Weights shared via torrent and via HuggingFace
field_rldata_class: closed
field_rldata_link: https://huggingface.co/mistralai/Mixtral-8x7B-v0.1/tree/main
field_rldata_notes: No information provided online or in the preprint
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1/tree/main
field_license_class: open
field_license_link: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1/blob/main/README.md
field_license_notes: Apache 2.0
field_code_class: closed
field_code_link: https://github.com/mistralai/mistral-src
field_architecture_class: partial
field_architecture_link: https://github.com/mistralai/mistral-src
field_architecture_notes: Some information on architecture provided in github repo and in preprint
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2401.04088
data:
{"project": {"name": "Mixtral 8x7B Instruct", "link": "https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1", "notes": null, "llmbase": "Mistral", "rlbase": "Unspecified", "license": "Apache 2.0"}, "org": {"name": "Mistral AI", "link": "https://mistral.ai", "notes": null}, "opencode": {"class": "closed", "link": null, "notes": "No training code for Mixtral 8x7B made available"}, "llmdata": {"class": "closed", "link": null, "notes": "No information provided on pretraining data"}, "llmweights": {"class": "open", "link": "https://huggingface.co/mistralai/Mixtral-8x7B-v0.1/tree/main", "notes": "Weights shared via torrent and via HuggingFace"}, "rldata": {"class": "closed", "link": "https://huggingface.co/mistralai/Mixtral-8x7B-v0.1/tree/main", "notes": "No information provided online or in the preprint"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1/tree/main", "notes": "Instruct version of model weights made available but no information on fine-tuning procedure provided"}, "license": {"class": "open", "link": "https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1/blob/main/README.md", "notes": "Apache 2.0"}, "code": {"class": "closed", "link": "https://github.com/mistralai/mistral-src", "notes": "the little code that is available is uncommented and undocumented, and relates to a reference implementation of the 7B version"}, "architecture": {"class": "partial", "link": "https://github.com/mistralai/mistral-src", "notes": "Some information on architecture provided in github repo and in preprint"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2401.04088", "notes": "Preprint describes mixture of experts and evalutaion but provides no details about pretraining datasets, instruction tuning datasets, or fine-tuning process, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer reviewed paper available"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card available, HuggingFace modelcard just points to a corporate blog post"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet available"}, "package": {"class": "partial", "link": "https://docs.mistral.ai/quickstart/", "notes": "Docker image shared on github"}, "api": {"class": "closed", "link": "https://console.mistral.ai/", "notes": "Only paid API access available"}}

field_rlweights_notes:
Instruct version of model weights made available but no information on fine-tuning procedure provided

field_code_notes:
the little code that is available is uncommented and undocumented, and relates to a reference implementation of the 7B version

field_preprint_notes:
Preprint describes mixture of experts and evalutaion but provides no details about pretraining datasets, instruction tuning datasets, or fine-tuning process, hence partial.


id: solar-70B
git_filename: projects/solar-70B.yaml
format: yaml
field_project_name: Solar 70B
field_project_link: https://huggingface.co/upstage/SOLAR-0-70b-16bit
field_project_notes: HuggingFace profile says 'Solar is a great example of the progress enabled by open source.'
field_project_llmbase: LLaMA2
field_project_rlbase: Orca-style, Alpaca-style
field_project_license: Meta Community license, CC-BY-NC
field_org_name: Upstage AI
field_org_link: https://en.upstage.ai/
field_org_notes: Korean venture
field_opencode_class: closed
field_opencode_notes: No code repository found
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rldata_notes: No RLHF datasets specified or shared, docs say 'Orca-style dataset, Alpaca-style dataset'
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/upstage/SOLAR-0-70b-16bit/tree/main
field_rlweights_notes: Finetuned checkpoints only shared through CC-BY-NC
field_license_class: closed
field_license_link: https://huggingface.co/upstage/SOLAR-0-70b-16bit#model-details
field_license_notes: Meta Community License for base model, and CC-BY-NC 4.0 for fine-tuned model weights
field_code_class: closed
field_code_notes: HuggingFace code only comprises configuration json; no documentation available.
field_architecture_class: closed
field_architecture_link: https://huggingface.co/upstage/SOLAR-0-70b-16bit
field_architecture_notes: Precise architecture, training, fine-tuning procedures not given.
field_preprint_class: closed
data:
{"project": {"name": "Solar 70B", "link": "https://huggingface.co/upstage/SOLAR-0-70b-16bit", "notes": "HuggingFace profile says 'Solar is a great example of the progress enabled by open source.'", "llmbase": "LLaMA2", "rlbase": "Orca-style, Alpaca-style", "license": "Meta Community license, CC-BY-NC"}, "org": {"name": "Upstage AI", "link": "https://en.upstage.ai/", "notes": "Korean venture"}, "opencode": {"class": "closed", "link": null, "notes": "No code repository found"}, "llmdata": {"class": "closed", "link": null, "notes": "Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "No RLHF datasets specified or shared, docs say 'Orca-style dataset, Alpaca-style dataset'"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/upstage/SOLAR-0-70b-16bit/tree/main", "notes": "Finetuned checkpoints only shared through CC-BY-NC"}, "license": {"class": "closed", "link": "https://huggingface.co/upstage/SOLAR-0-70b-16bit#model-details", "notes": "Meta Community License for base model, and CC-BY-NC 4.0 for fine-tuned model weights"}, "code": {"class": "closed", "link": null, "notes": "HuggingFace code only comprises configuration json; no documentation available."}, "architecture": {"class": "closed", "link": "https://huggingface.co/upstage/SOLAR-0-70b-16bit", "notes": "Precise architecture, training, fine-tuning procedures not given."}, "preprint": {"class": "closed", "link": null, "notes": "No preprint or any form of scientific docuentation found."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/upstage/SOLAR-0-70b-16bit", "notes": "HuggingFace model card used mostly as advertising, omits many details on training, fine-tuning, evaluation."}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "API only available by signing up for 'private LLM' service"}}

field_llmdata_notes:
Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_modelcard_notes:
HuggingFace model card used mostly as advertising, omits many details on training, fine-tuning, evaluation.


id: airoboros
git_filename: projects/airoboros.yaml
format: yaml
field_project_name: Airoboros L2 70B GPT4
field_project_link: https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1
field_project_llmbase: Llama2
field_project_rlbase: Airoboros (synthetic)
field_project_license: Purposely left ambiguous
field_org_name: Jon Durbin
field_org_link: https://github.com/jondurbin
field_org_notes: Only active on GitHub since May 2023
field_opencode_class: partial
field_opencode_link: https://gist.github.com/jondurbin/87fc040b92a3073125ed516b04bc6e19
field_opencode_notes: Repo exists for RL data but only a gist exists for model training and architecture
field_llmdata_class: closed
field_llmdata_notes: Llama2 training data is nowhere documented or disclosed
field_llmweights_class: partial
field_llmweights_notes: Llama2, made conditionally available by Meta
field_rldata_class: open
field_rldata_link: https://github.com/jondurbin/airoboros
field_rldata_notes: Airoboros, an implementation of the Self-Instruct paper
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1/tree/main
field_rlweights_notes: Made available through HuggingFace
field_license_class: partial
field_license_link: https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1#licence-and-usage-restrictions
field_license_notes: Licensing left ambiguous because of murky status of OpenAI-derived Self-Instruct data
field_code_class: partial
field_code_notes: What little code available is not very systematically documented
field_architecture_class: partial
field_architecture_link: https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1/discussions/2#64c29e4c617b36543dedac9a
field_architecture_notes: Some info can be gleaned at link but most remains undocumented
data:
{"project": {"name": "Airoboros L2 70B GPT4", "link": "https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1", "notes": null, "llmbase": "Llama2", "rlbase": "Airoboros (synthetic)", "license": "Purposely left ambiguous"}, "org": {"name": "Jon Durbin", "link": "https://github.com/jondurbin", "notes": "Only active on GitHub since May 2023"}, "opencode": {"class": "partial", "link": "https://gist.github.com/jondurbin/87fc040b92a3073125ed516b04bc6e19", "notes": "Repo exists for RL data but only a gist exists for model training and architecture"}, "llmdata": {"class": "closed", "link": null, "notes": "Llama2 training data is nowhere documented or disclosed"}, "llmweights": {"class": "partial", "link": null, "notes": "Llama2, made conditionally available by Meta"}, "rldata": {"class": "open", "link": "https://github.com/jondurbin/airoboros", "notes": "Airoboros, an implementation of the Self-Instruct paper"}, "rlweights": {"class": "open", "link": "https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1/tree/main", "notes": "Made available through HuggingFace"}, "license": {"class": "partial", "link": "https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1#licence-and-usage-restrictions", "notes": "Licensing left ambiguous because of murky status of OpenAI-derived Self-Instruct data"}, "code": {"class": "partial", "link": null, "notes": "What little code available is not very systematically documented"}, "architecture": {"class": "partial", "link": "https://huggingface.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1/discussions/2#64c29e4c617b36543dedac9a", "notes": "Some info can be gleaned at link but most remains undocumented"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/jondurbin/airoboros-65b-gpt4-1.4", "notes": "Instructs reader to look up model card for prior 65B Llama1 version"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/jondurbin/airoboros-gpt4-1.4.1", "notes": "Datasheet for RL data only"}, "package": {"class": "closed", "link": null, "notes": "No package found"}, "api": {"class": "closed", "link": null, "notes": "No API found"}}


id: qwen-1.5-chat
git_filename: projects/qwen-1.5-chat.yaml
format: yaml
field_project_name: Qwen 1.5
field_project_link: https://qwenlm.github.io/blog/qwen1.5/
field_project_notes: This is based on the 72B version, the largest of 8 available model sizes.
field_project_llmbase: QwenLM
field_project_rlbase: Unspecified
field_project_license: Qianwen License
field_org_name: Alibaba Cloud
field_opencode_class: partial
field_opencode_link: https://github.com/QwenLM/Qwen1.5/
field_opencode_notes: Repository provides sparse source code and some examples for SFT
field_llmdata_class: closed
field_llmdata_notes: Pretraining data not specified or documented.
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/Qwen/Qwen1.5-72B/tree/main
field_llmweights_notes: Also available in smaller model sizes
field_rldata_class: closed
field_rldata_link: https://qwen.readthedocs.io/en/latest/training/SFT/llama_factory.html
field_rldata_notes: Data not specified or documented. Some example code in repo provides directions but no details.
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/Qwen/Qwen1.5-72B-Chat/tree/main
field_rlweights_notes: Also available in smaller model sizes
field_license_class: closed
field_license_notes: Qianwen License
field_code_class: partial
field_code_notes: Repository is fairly well-documented.
field_architecture_class: partial
field_architecture_notes: No clear description of architecture found.
field_preprint_class: closed
field_preprint_notes: No preprint found.
data:
{"project": {"name": "Qwen 1.5", "link": "https://qwenlm.github.io/blog/qwen1.5/", "notes": "This is based on the 72B version, the largest of 8 available model sizes.", "llmbase": "QwenLM", "rlbase": "Unspecified", "license": "Qianwen License"}, "org": {"name": "Alibaba Cloud", "link": null, "notes": "Qwen (abbr. for Tongyi Qianwen \u901a\u4e49\u5343\u95ee) refers to the large language model family built by Alibaba Cloud"}, "opencode": {"class": "partial", "link": "https://github.com/QwenLM/Qwen1.5/", "notes": "Repository provides sparse source code and some examples for SFT"}, "llmdata": {"class": "closed", "link": null, "notes": "Pretraining data not specified or documented."}, "llmweights": {"class": "open", "link": "https://huggingface.co/Qwen/Qwen1.5-72B/tree/main", "notes": "Also available in smaller model sizes"}, "rldata": {"class": "closed", "link": "https://qwen.readthedocs.io/en/latest/training/SFT/llama_factory.html", "notes": "Data not specified or documented. Some example code in repo provides directions but no details."}, "rlweights": {"class": "open", "link": "https://huggingface.co/Qwen/Qwen1.5-72B-Chat/tree/main", "notes": "Also available in smaller model sizes"}, "license": {"class": "closed", "link": null, "notes": "Qianwen License"}, "code": {"class": "partial", "link": null, "notes": "Repository is fairly well-documented."}, "architecture": {"class": "partial", "link": null, "notes": "No clear description of architecture found."}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found."}, "modelcard": {"class": "closed", "link": null, "notes": "Model card on HF only serves as a pointer to the model, no actual info provided."}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet."}, "package": {"class": "partial", "link": null, "notes": "No specific package provided but integrates well with many widely used packages"}, "api": {"class": "open", "link": null, "notes": "Available through various APIs"}}

field_org_notes:
Qwen (abbr. for Tongyi Qianwen 通义千问) refers to the large language model family built by Alibaba Cloud


id: cerebras-gpt-111m-instruction
git_filename: projects/cerebras-gpt-111m-instruction.yaml
format: yaml
field_project_name: Cerebras GPT 111M Instruction
field_project_link: https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction
field_project_llmbase: Cerebras
field_project_rlbase: Alpaca (synthetic)
field_project_license: Apache 2.0
field_org_name: Cerebras + Schramm
field_org_link: https://github.com/Cerebras
field_opencode_class: partial
field_opencode_link: https://github.com/Cerebras/gigaGPT
field_opencode_notes: Some of the training code available in GigaGPT, but fine-tuning
field_llmdata_class: open
field_llmdata_link: https://huggingface.co/datasets/EleutherAI/pile
field_llmdata_notes: Eleuther AI's The Pile
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/cerebras/Cerebras-GPT-111M
field_llmweights_notes: base model available via Cerebras
field_rldata_class: open
field_rldata_link: https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM/blob/main/data/alpaca_gpt4_data.json
field_rldata_notes: Alpaca GPT4
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction/tree/main
field_rlweights_notes: Finetuned model weights available
field_license_class: partial
field_license_link: https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction/
field_license_notes: Licensing situation unclear as model page mentions no license (base model is licensed Apache 2.0)
field_code_class: closed
field_code_notes: Code only sparsely documented
field_architecture_class: open
field_architecture_notes: Described in preprint
data:
{"project": {"name": "Cerebras GPT 111M Instruction", "link": "https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction", "notes": null, "llmbase": "Cerebras", "rlbase": "Alpaca (synthetic)", "license": "Apache 2.0"}, "org": {"name": "Cerebras + Schramm", "link": "https://github.com/Cerebras", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/Cerebras/gigaGPT", "notes": "Some of the training code available in GigaGPT, but fine-tuning"}, "llmdata": {"class": "open", "link": "https://huggingface.co/datasets/EleutherAI/pile", "notes": "Eleuther AI's The Pile"}, "llmweights": {"class": "open", "link": "https://huggingface.co/cerebras/Cerebras-GPT-111M", "notes": "base model available via Cerebras"}, "rldata": {"class": "open", "link": "https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM/blob/main/data/alpaca_gpt4_data.json", "notes": "Alpaca GPT4"}, "rlweights": {"class": "open", "link": "https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction/tree/main", "notes": "Finetuned model weights available"}, "license": {"class": "partial", "link": "https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction/", "notes": "Licensing situation unclear as model page mentions no license (base model is licensed Apache 2.0)"}, "code": {"class": "closed", "link": null, "notes": "Code only sparsely documented"}, "architecture": {"class": "open", "link": null, "notes": "Described in preprint"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2304.03208", "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": "https://huggingface.co/cerebras/Cerebras-GPT-111M", "notes": "Only serves as as advertising for the model"}, "datasheet": {"class": "open", "link": "https://arxiv.org/abs/2201.07311", "notes": "Datasheet available for The Pile"}, "package": {"class": "closed", "link": null, "notes": "No package found"}, "api": {"class": "open", "link": null, "notes": "Available through HuggingFace inference API"}}


id: wizardlm-7B-V1
git_filename: projects/wizardlm-7B-V1.yaml
format: yaml
field_project_name: WizardLM-7B
field_project_link: https://github.com/nlpxucan/WizardLM
field_project_notes: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
field_project_llmbase: LLaMA-7B
field_project_rlbase: Evol-Instruct (synthetic)
field_project_license: CC-BY-NC-4.0
field_org_name: Microsoft & Peking University
field_org_link: https://github.com/nlpxucan
field_opencode_class: partial
field_opencode_link: https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
field_opencode_notes: Fast-evolving repository contains WizardLM code
field_llmdata_class: partial
field_llmdata_notes: Based on LLaMA, which is claimed to be public but nowhere exactly documented.
field_llmweights_class: closed
field_rldata_class: open
field_rldata_link: https://github.com/nlpxucan/WizardLM/tree/main/WizardLM#training-data
field_rldata_notes: The Evol-Instruct dataset contains 70k instruction-following sequences generated from Evol-Instruct
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/WizardLM/WizardLM-7B-V1.0/tree/main
field_rlweights_notes: Model weights offered as a delta to LLaMA
field_license_class: partial
field_license_link: https://github.com/nlpxucan/WizardLM/blob/main/WizardLM/MODEL_DIFF_LICENSE
field_code_class: partial
field_code_link: https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
field_code_notes: Code is only partially documented, not clearly versioned, and appears to be in flux.
field_architecture_class: open
field_architecture_link: https://arxiv.org/abs/2304.12244
field_architecture_notes: Architecture described in preprint and partly accessible in code repository
field_preprint_class: open
data:
{"project": {"name": "WizardLM-7B", "link": "https://github.com/nlpxucan/WizardLM", "notes": "Empowering Large Pre-Trained Language Models to Follow Complex Instructions", "llmbase": "LLaMA-7B", "rlbase": "Evol-Instruct (synthetic)", "license": "CC-BY-NC-4.0"}, "org": {"name": "Microsoft & Peking University", "link": "https://github.com/nlpxucan", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/tree/main/WizardLM", "notes": "Fast-evolving repository contains WizardLM code"}, "llmdata": {"class": "partial", "link": null, "notes": "Based on LLaMA, which is claimed to be public but nowhere exactly documented."}, "llmweights": {"class": "closed", "link": null, "notes": "Based on LLaMA weights, which are not openly available though a leaked versions is in wide circulation."}, "rldata": {"class": "open", "link": "https://github.com/nlpxucan/WizardLM/tree/main/WizardLM#training-data", "notes": "The Evol-Instruct dataset contains 70k instruction-following sequences generated from Evol-Instruct"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/WizardLM/WizardLM-7B-V1.0/tree/main", "notes": "Model weights offered as a delta to LLaMA"}, "license": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/blob/main/WizardLM/MODEL_DIFF_LICENSE", "notes": "Restricted for academic research purposes only. Code and Model diff release under CC-BY-NC-4.0, software code under Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/nlpxucan/WizardLM/tree/main/WizardLM", "notes": "Code is only partially documented, not clearly versioned, and appears to be in flux."}, "architecture": {"class": "open", "link": "https://arxiv.org/abs/2304.12244", "notes": "Architecture described in preprint and partly accessible in code repository"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2304.12244", "notes": "Preprint describes method for creating large amounts of LLM-based synthetic RLHF data and fine-tuning WizardLM based on it"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper or data audit found"}, "modelcard": {"class": "closed", "link": "https://huggingface.co/WizardLM/WizardLM-7B-V1.0", "notes": "Model card is only a placeholder and generates an error (missing yaml metadata)"}, "datasheet": {"class": "closed", "link": "https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k", "notes": "Dataset card for Evol-Instruct generates an error"}, "package": {"class": "closed", "link": null, "notes": "No package available"}, "api": {"class": "closed", "link": null, "notes": "No API available"}}

field_llmweights_notes:
Based on LLaMA weights, which are not openly available though a leaked versions is in wide circulation.

field_license_notes:
Restricted for academic research purposes only. Code and Model diff release under CC-BY-NC-4.0, software code under Apache 2.0

field_preprint_notes:
Preprint describes method for creating large amounts of LLM-based synthetic RLHF data and fine-tuning WizardLM based on it


id: text-generation-webui
git_filename: projects/text-generation-webui.yaml
format: yaml
field_project_link: https://github.com/oobabooga/text-generation-webui
field_project_notes: not an LLM RLHF model
field_project_llmbase: various
field_project_rlbase: various
field_project_license: GNU Affero General Public License v3.0
field_org_name: Oobabooga
field_org_link: https://oobabooga.github.io
field_opencode_class: open
field_llmdata_class: open
field_llmdata_link: https://huggingface.co/models?sort=downloads&search=eleutherai%2Fpythia+deduped
field_llmweights_class: open
field_rldata_class: closed
field_rlweights_class: closed
field_license_class: open
field_code_class: open
field_architecture_class: closed
field_preprint_class: closed
field_paper_class: closed
field_modelcard_class: closed
field_datasheet_class: closed
field_package_class: closed
field_api_class: closed
data:
{"project": {"name": null, "link": "https://github.com/oobabooga/text-generation-webui", "notes": "not an LLM RLHF model", "llmbase": "various", "rlbase": "various", "license": "GNU Affero General Public License v3.0"}, "org": {"name": "Oobabooga", "link": "https://oobabooga.github.io", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "open", "link": "https://huggingface.co/models?sort=downloads&search=eleutherai%2Fpythia+deduped", "notes": null}, "llmweights": {"class": "open", "link": null, "notes": null}, "rldata": {"class": "closed", "link": null, "notes": null}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": null}, "code": {"class": "open", "link": null, "notes": null}, "architecture": {"class": "closed", "link": null, "notes": null}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "closed", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}


id: Xwin-LM
git_filename: projects/Xwin-LM.yaml
format: yaml
field_project_name: Xwin-LM
field_project_link: https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1
field_project_notes: Xwin-LM aims to develop and open-source alignment technologies for large language models
field_project_llmbase: LLaMA2
field_project_rlbase: unknown
field_project_license: Llama 2 license
field_org_name: Xwin-LM
field_org_link: https://github.com/Xwin-LM
field_org_notes: Xwin-LM aims to develop and open-source alignment technologies for large language models
field_opencode_class: closed
field_opencode_link: https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1
field_opencode_notes: HuggingFace page notes 'to do ":" Release the source code'
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rlweights_class: closed
field_rlweights_link: https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1/tree/main
field_rlweights_notes: Downloadable model presumably includes RLHF tuning but no documentation available
field_license_class: closed
field_license_link: https://github.com/facebookresearch/llama/blob/main/LICENSE
field_license_notes: Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license
field_code_class: closed
field_code_notes: No documentation available.
field_architecture_class: closed
field_architecture_link: https://github.com/Xwin-LM/Xwin-LM#news
field_architecture_notes: No information available beyond that it is based on Llama and "RLHF plays crucial role"
field_preprint_class: closed
data:
{"project": {"name": "Xwin-LM", "link": "https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1", "notes": "Xwin-LM aims to develop and open-source alignment technologies for large language models", "llmbase": "LLaMA2", "rlbase": "unknown", "license": "Llama 2 license"}, "org": {"name": "Xwin-LM", "link": "https://github.com/Xwin-LM", "notes": "Xwin-LM aims to develop and open-source alignment technologies for large language models"}, "opencode": {"class": "closed", "link": "https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1", "notes": "HuggingFace page notes 'to do \":\" Release the source code'"}, "llmdata": {"class": "closed", "link": null, "notes": "Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "RLHF data for Llama includes 1 million Meta-specific tuning prompts not made available, no other details known about RLHF and alignment tuning added by Xwin-LM"}, "rlweights": {"class": "closed", "link": "https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1/tree/main", "notes": "Downloadable model presumably includes RLHF tuning but no documentation available"}, "license": {"class": "closed", "link": "https://github.com/facebookresearch/llama/blob/main/LICENSE", "notes": "Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license"}, "code": {"class": "closed", "link": null, "notes": "No documentation available."}, "architecture": {"class": "closed", "link": "https://github.com/Xwin-LM/Xwin-LM#news", "notes": "No information available beyond that it is based on Llama and \"RLHF plays crucial role\""}, "preprint": {"class": "closed", "link": "https://github.com/Xwin-LM/Xwin-LM#news", "notes": "No preprint available; \"Coming soon (Stay tuned)\""}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper available"}, "modelcard": {"class": "closed", "link": "https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1", "notes": "HuggingFace \"model card\" used to advertise model, but no details available."}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "API available through vllm and HuggingFace"}}

field_llmdata_notes:
Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_rldata_notes:
RLHF data for Llama includes 1 million Meta-specific tuning prompts not made available, no other details known about RLHF and alignment tuning added by Xwin-LM


id: Falcon-40B-instruct
git_filename: projects/Falcon-40B-instruct.yaml
format: yaml
field_project_name: Falcon-40B-instruct
field_project_link: https://huggingface.co/tiiuae/falcon-40b-instruct
field_project_llmbase: Falcon 40B
field_project_rlbase: Baize (synthetic)
field_project_license: Apache 2.0 license
field_org_name: Technology Innovation Institute
field_org_link: https://falconllm.tii.ae
field_opencode_class: closed
field_opencode_link: https://huggingface.co/tiiuae/falcon-40b-instruct
field_opencode_notes: No source code shared, even though the term "open source" is used.
field_llmdata_class: partial
field_llmdata_link: https://huggingface.co/datasets/tiiuae/falcon-refinedweb
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/tiiuae/falcon-40b-instruct/tree/main
field_llmweights_notes: Model weights available through HuggingFace library
field_rldata_class: partial
field_rldata_link: https://github.com/project-baize/baize-chatbot
field_rlweights_class: closed
field_rlweights_link: https://github.com/project-baize/baize-chatbot#v1
field_rlweights_notes: No RL weights or checkpoints made available
field_license_class: open
field_code_class: closed
field_code_notes: No source code found, therefore no documentation found.
field_architecture_class: partial
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2306.01116
field_paper_class: closed
field_paper_notes: No peer-reviewed paper known.
field_modelcard_class: partial
data:
{"project": {"name": "Falcon-40B-instruct", "link": "https://huggingface.co/tiiuae/falcon-40b-instruct", "notes": null, "llmbase": "Falcon 40B", "rlbase": "Baize (synthetic)", "license": "Apache 2.0 license"}, "org": {"name": "Technology Innovation Institute", "link": "https://falconllm.tii.ae", "notes": null}, "opencode": {"class": "closed", "link": "https://huggingface.co/tiiuae/falcon-40b-instruct", "notes": "No source code shared, even though the term \"open source\" is used."}, "llmdata": {"class": "partial", "link": "https://huggingface.co/datasets/tiiuae/falcon-refinedweb", "notes": "From the documentation 'The key ingredient for the high quality of the Falcon models is their training data, predominantly based (>80%) on RefinedWeb \u2014 a novel massive web dataset based on CommonCrawl' (https://huggingface.co/blog/falcon). However, only a small sample is made available."}, "llmweights": {"class": "open", "link": "https://huggingface.co/tiiuae/falcon-40b-instruct/tree/main", "notes": "Model weights available through HuggingFace library"}, "rldata": {"class": "partial", "link": "https://github.com/project-baize/baize-chatbot", "notes": "RL data inherited from Baize but provenance not well-documented. From the documentation 'Falcon-40B-Instruct was finetuned on a 150M tokens from Baize mixed with 5% of RefinedWeb data.'"}, "rlweights": {"class": "closed", "link": "https://github.com/project-baize/baize-chatbot#v1", "notes": "No RL weights or checkpoints made available"}, "license": {"class": "open", "link": null, "notes": "First release came with a legally murky license that was swiftly criticised and now generates a 404. Current documentation 'Falcon-40B-Instruct is made available under the Apache 2.0 license.'"}, "code": {"class": "closed", "link": null, "notes": "No source code found, therefore no documentation found."}, "architecture": {"class": "partial", "link": null, "notes": "Architecture sketched on HuggingFace as \"Falcon-40B-Instruct is a 40B parameters causal decoder-only model built by TII based on Falcon-40B and finetuned on a mixture of Baize.\""}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2306.01116", "notes": "Preprint covers the creation and curation of RefinedWeb dataset, but not other aspects of the model, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper known."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/tiiuae/falcon-40b-instruct", "notes": "Model card on HuggingFace is mostly used to advertise the model, not to document its training and evaluation details."}, "datasheet": {"class": "closed", "link": null, "notes": "There is no datasheet available."}, "package": {"class": "closed", "link": null, "notes": "There is no package."}, "api": {"class": "closed", "link": "https://huggingface.co/tiiuae/falcon-40b-instruct", "notes": "There is no API, and HuggingFace inference API is disabled for this model."}}

field_llmdata_notes:
From the documentation 'The key ingredient for the high quality of the Falcon models is their training data, predominantly based (>80%) on RefinedWeb — a novel massive web dataset based on CommonCrawl' (https://huggingface.co/blog/falcon). However, only a small sample is made available.

field_rldata_notes:
RL data inherited from Baize but provenance not well-documented. From the documentation 'Falcon-40B-Instruct was finetuned on a 150M tokens from Baize mixed with 5% of RefinedWeb data.'

field_license_notes:
First release came with a legally murky license that was swiftly criticised and now generates a 404. Current documentation 'Falcon-40B-Instruct is made available under the Apache 2.0 license.'

field_architecture_notes:
Architecture sketched on HuggingFace as "Falcon-40B-Instruct is a 40B parameters causal decoder-only model built by TII based on Falcon-40B and finetuned on a mixture of Baize."

field_preprint_notes:
Preprint covers the creation and curation of RefinedWeb dataset, but not other aspects of the model, hence partial.

field_modelcard_notes:
Model card on HuggingFace is mostly used to advertise the model, not to document its training and evaluation details.


id: bloomz
git_filename: projects/bloomz.yaml
format: yaml
field_project_name: BLOOMZ
field_project_link: https://huggingface.co/bigscience/bloomz
field_project_llmbase: BLOOMZ, mT0
field_project_rlbase: xP3
field_project_license: Apache 2.0 and RAIL (responsible AI license)
field_org_name: bigscience-workshop
field_org_link: https://github.com/bigscience-workshop
field_opencode_class: open
field_opencode_link: https://github.com/bigscience-workshop/xmtf
field_opencode_notes: Repository provides a guided overview to all components
field_llmdata_class: open
field_llmdata_link: https://github.com/bigscience-workshop/xmtf#data
field_llmdata_notes: Data made available & documented in detail in repo and preprint
field_llmweights_class: open
field_llmweights_link: https://github.com/bigscience-workshop/xmtf#models
field_llmweights_notes: Model made available on github
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/bigscience/xP3all
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/bigscience/bloomz-optimizer-states/tree/main
field_rlweights_notes: Fine-tuned checkpoint available for download
field_license_class: partial
field_license_link: https://bigscience.huggingface.co/blog/the-bigscience-rail-license
field_code_class: open
field_code_link: https://github.com/bigscience-workshop/xmtf
field_code_notes: Code well documented and actively maintained
field_architecture_class: open
field_architecture_link: https://github.com/bigscience-workshop/xmtf#create-xp3x
field_architecture_notes: Architecture described in preprint, code available in github repo, recipe on HuggingFace
data:
{"project": {"name": "BLOOMZ", "link": "https://huggingface.co/bigscience/bloomz", "notes": null, "llmbase": "BLOOMZ, mT0", "rlbase": "xP3", "license": "Apache 2.0 and RAIL (responsible AI license)"}, "org": {"name": "bigscience-workshop", "link": "https://github.com/bigscience-workshop", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/bigscience-workshop/xmtf", "notes": "Repository provides a guided overview to all components"}, "llmdata": {"class": "open", "link": "https://github.com/bigscience-workshop/xmtf#data", "notes": "Data made available & documented in detail in repo and preprint"}, "llmweights": {"class": "open", "link": "https://github.com/bigscience-workshop/xmtf#models", "notes": "Model made available on github"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/bigscience/xP3all", "notes": "From the documentation 'xP3 (Crosslingual Public Pool of Prompts) is a collection of prompts & datasets across 46 of languages & 16 NLP tasks'"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/bigscience/bloomz-optimizer-states/tree/main", "notes": "Fine-tuned checkpoint available for download"}, "license": {"class": "partial", "link": "https://bigscience.huggingface.co/blog/the-bigscience-rail-license", "notes": "Code licensed under Apache 2.0, model under bespoke 'Responsible AI License' which imposes some limitations"}, "code": {"class": "open", "link": "https://github.com/bigscience-workshop/xmtf", "notes": "Code well documented and actively maintained"}, "architecture": {"class": "open", "link": "https://github.com/bigscience-workshop/xmtf#create-xp3x", "notes": "Architecture described in preprint, code available in github repo, recipe on HuggingFace"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2211.05100", "notes": "Preprint (updated June 2023) of 65 pages + 10 page appendix"}, "paper": {"class": "open", "link": "https://aclanthology.org/2023.acl-long.891/", "notes": "Peer-reviewed paper of 9 pages + 114 page appendix describes the multitask finetuning (instruction tuning) of BLOOM (see preprint) to form BLOOMZ"}, "modelcard": {"class": "open", "link": "https://huggingface.co/bigscience/bloomz", "notes": "Model card"}, "datasheet": {"class": "open", "link": "https://huggingface.co/datasets/bigscience/xP3", "notes": "Dataset documented in dataset card at HuggingFace"}, "package": {"class": "closed", "link": null, "notes": "No packages published"}, "api": {"class": "open", "link": "https://huggingface.co/spaces/bigscience/petals-api", "notes": "Petals API via HuggingFace not always available ('not enough hardware capacity')"}}

field_rldata_notes:
From the documentation 'xP3 (Crosslingual Public Pool of Prompts) is a collection of prompts & datasets across 46 of languages & 16 NLP tasks'

field_license_notes:
Code licensed under Apache 2.0, model under bespoke 'Responsible AI License' which imposes some limitations

field_paper_notes:
Peer-reviewed paper of 9 pages + 114 page appendix describes the multitask finetuning (instruction tuning) of BLOOM (see preprint) to form BLOOMZ


id: llama-3.1
git_filename: projects/llama-3.1.yaml
format: yaml
field_project_name: Llama 3.1
field_project_link: https://huggingface.co/meta-llama/Meta-Llama-3.1-405B
field_project_llmbase: Meta Llama 3
field_project_rlbase: Meta, undocumented
field_project_license: Meta Llama 3 Community License
field_org_name: Facebook Research
field_org_link: https://github.com/facebookresearch
field_opencode_class: partial
field_opencode_link: https://github.com/meta-llama/llama3
field_opencode_notes: Repository only offers code for inference pipeline
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B
field_rldata_class: closed
field_rldata_notes: No information available on instruction-tuning.
field_rlweights_class: closed
field_license_class: closed
field_license_link: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B
field_code_class: partial
field_architecture_class: partial
field_architecture_link: https://ai.meta.com/research/publications/the-llama-3-herd-of-models/
field_preprint_class: closed
field_preprint_notes: No preprint or any other scientific documentation available.
field_paper_class: closed
field_paper_notes: No peer-reviewed paper available.
field_modelcard_class: partial
field_modelcard_link: https://huggingface.co/meta-llama/Meta-Llama-3.1-405B
field_modelcard_notes: There is a model card, but it does not disclose the training process
field_datasheet_class: closed
data:
{"project": {"name": "Llama 3.1", "link": "https://huggingface.co/meta-llama/Meta-Llama-3.1-405B", "notes": null, "llmbase": "Meta Llama 3", "rlbase": "Meta, undocumented", "license": "Meta Llama 3 Community License"}, "org": {"name": "Facebook Research", "link": "https://github.com/facebookresearch", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/meta-llama/llama3", "notes": "Repository only offers code for inference pipeline"}, "llmdata": {"class": "closed", "link": null, "notes": "Data nowhere disclosed or documented, and described in the llama 3.1 paper as \"obtained from the web\""}, "llmweights": {"class": "partial", "link": "https://huggingface.co/meta-llama/Meta-Llama-3.1-8B", "notes": "Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license"}, "rldata": {"class": "closed", "link": null, "notes": "No information available on instruction-tuning."}, "rlweights": {"class": "closed", "link": null, "notes": "Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license"}, "license": {"class": "closed", "link": "https://huggingface.co/meta-llama/Meta-Llama-3.1-8B", "notes": "Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license"}, "code": {"class": "partial", "link": null, "notes": "Code provide only model architecture and an inferencing pipeline examples; some files are documented."}, "architecture": {"class": "partial", "link": "https://ai.meta.com/research/publications/the-llama-3-herd-of-models/", "notes": "Architecture described in paper, energy consumtion and environmental impact disclosed in model card, but not in paper; training process not fully documented"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint or any other scientific documentation available."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper available."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/meta-llama/Meta-Llama-3.1-405B", "notes": "There is a model card, but it does not disclose the training process"}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided at all"}, "package": {"class": "open", "link": "https://pypi.org/project/llama-models/", "notes": "Package is provided in Pypi"}, "api": {"class": "partial", "link": "https://www.meta.ai/?utm_source=ai_meta_site&utm_medium=web&utm_content=AI_nav&utm_campaign=April_moment", "notes": "API only available behind a privacy-defying signup form"}}

field_llmdata_notes:
Data nowhere disclosed or documented, and described in the llama 3.1 paper as "obtained from the web"

field_llmweights_notes:
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license

field_rlweights_notes:
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license

field_license_notes:
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license

field_code_notes:
Code provide only model architecture and an inferencing pipeline examples; some files are documented.

field_architecture_notes:
Architecture described in paper, energy consumtion and environmental impact disclosed in model card, but not in paper; training process not fully documented

field_api_link:
https://www.meta.ai/?utm_source=ai_meta_site&utm_medium=web&utm_content=AI_nav&utm_campaign=April_moment


id: ChatGLM-6B
git_filename: projects/ChatGLM-6B.yaml
format: yaml
field_project_name: ChatGLM-6B
field_project_link: https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md
field_project_llmbase: GLM (own)
field_project_rlbase: Unspecified
field_project_license: Apache 2.0
field_org_name: THUDM
field_org_link: https://github.com/THUDM
field_org_notes: Knowledge Engineering Group (KEG) & Data Mining at Tsinghua University
field_opencode_class: partial
field_opencode_link: https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md#deployment
field_opencode_notes: Some code made available on Github
field_llmdata_class: partial
field_llmdata_link: http://doi.org/10.18653/v1/2022.acl-long.26
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/THUDM/chatglm-6b/tree/main
field_llmweights_notes: Model made available through HuggingFace
field_rldata_class: closed
field_rlweights_class: closed
field_rlweights_notes: No weights or checkpoints corresponding to the delta of the LLM vs RLHF provided
field_license_class: open
field_license_link: https://github.com/THUDM/ChatGLM-6B/blob/main/LICENSE
field_license_notes: Apache 2.0
field_code_class: partial
field_code_link: https://github.com/THUDM/ChatGLM-6B/blob/main/ptuning/README_en.md
field_code_notes: Some documentation available, but a lot of code is not commented or explained.
field_architecture_class: partial
field_architecture_notes: Full details of architecture not specified in a single place
field_preprint_class: closed
field_paper_class: partial
data:
{"project": {"name": "ChatGLM-6B", "link": "https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md", "notes": "From the readme, \"ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese QA and dialogue. The model is trained for about 1T tokens of Chinese and English corpus, supplemented by supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback. With only about 6.2 billion parameters, the model is able to generate answers that are in line with human preference.\"", "llmbase": "GLM (own)", "rlbase": "Unspecified", "license": "Apache 2.0"}, "org": {"name": "THUDM", "link": "https://github.com/THUDM", "notes": "Knowledge Engineering Group (KEG) & Data Mining at Tsinghua University"}, "opencode": {"class": "partial", "link": "https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md#deployment", "notes": "Some code made available on Github"}, "llmdata": {"class": "partial", "link": "http://doi.org/10.18653/v1/2022.acl-long.26", "notes": "Training data not centrally made available, but described in 2022 ACL paper, appears to be mostly public datasets"}, "llmweights": {"class": "open", "link": "https://huggingface.co/THUDM/chatglm-6b/tree/main", "notes": "Model made available through HuggingFace"}, "rldata": {"class": "closed", "link": null, "notes": "docs mention \"supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback\", but none of the datasets used are clearly specified."}, "rlweights": {"class": "closed", "link": null, "notes": "No weights or checkpoints corresponding to the delta of the LLM vs RLHF provided"}, "license": {"class": "open", "link": "https://github.com/THUDM/ChatGLM-6B/blob/main/LICENSE", "notes": "Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/THUDM/ChatGLM-6B/blob/main/ptuning/README_en.md", "notes": "Some documentation available, but a lot of code is not commented or explained."}, "architecture": {"class": "partial", "link": null, "notes": "Full details of architecture not specified in a single place"}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "partial", "link": "https://aclanthology.org/2022.acl-long.26/", "notes": "ACL 2022 paper describes the training of the GLM base model, but the RLHF portion is more recent (there is also a related ICLR paper for a newer generation https://openreview.net/forum?id=-Aw0rrrPUF)"}, "modelcard": {"class": "closed", "link": "https://huggingface.co/THUDM/chatglm-6b", "notes": "No modelcard; the HuggingFace modelcard spot is used just as the homepage for the model."}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet"}, "package": {"class": "closed", "link": null, "notes": "No package"}, "api": {"class": "open", "link": "https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md#api-deployment", "notes": "API provided through fastapi uvicorn"}}

field_project_notes:
From the readme, "ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese QA and dialogue. The model is trained for about 1T tokens of Chinese and English corpus, supplemented by supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback. With only about 6.2 billion parameters, the model is able to generate answers that are in line with human preference."

field_llmdata_notes:
Training data not centrally made available, but described in 2022 ACL paper, appears to be mostly public datasets

field_rldata_notes:
docs mention "supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback", but none of the datasets used are clearly specified.

field_paper_notes:
ACL 2022 paper describes the training of the GLM base model, but the RLHF portion is more recent (there is also a related ICLR paper for a newer generation https://openreview.net/forum?id=-Aw0rrrPUF)


id: command-r
git_filename: projects/command-r.yaml
format: yaml
field_project_name: Command R+
field_project_link: https://huggingface.co/CohereForAI/c4ai-command-r-v01
field_project_rlbase: Aya Collection
field_project_license: CC-BY-NC and C4AI acceptable use policy
field_org_name: Cohere AI
field_org_link: https://cohere.com
field_opencode_class: closed
field_opencode_notes: No codebase available to study or adjust model architecture, training, or inner workings.
field_llmdata_class: closed
field_llmdata_link: https://docs.cohere.com/docs/data-statement
field_llmweights_class: closed
field_llmweights_notes: No checkpoint or model prior to SFT and instruction-tuning made available
field_rldata_class: open
field_rldata_link: https://huggingface.co/collections/CohereForAI/aya-datasets-660415741bd4852f01c81c77
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/CohereForAI/c4ai-command-r-v01/tree/main
field_rlweights_notes: Fine-tuned model weights made available for download
field_license_class: partial
field_license_link: https://docs.cohere.com/docs/c4ai-acceptable-use-policy
field_license_notes: Licensed under CC-BY-NC and requires agreeing to C4AI acceptable use policy
field_code_class: closed
field_code_notes: No source code available, so no documentation of code.
field_architecture_class: closed
field_architecture_notes: Architecture only sparsely documented.
field_preprint_class: closed
field_preprint_notes: No preprint appears to be made available at this time.
field_paper_class: closed
field_paper_notes: No paper known to document the Cohere Command R+ model or architecture.
field_modelcard_class: partial
data:
{"project": {"name": "Command R+", "link": "https://huggingface.co/CohereForAI/c4ai-command-r-v01", "notes": null, "llmbase": null, "rlbase": "Aya Collection", "license": "CC-BY-NC and C4AI acceptable use policy"}, "org": {"name": "Cohere AI", "link": "https://cohere.com", "notes": null}, "opencode": {"class": "closed", "link": null, "notes": "No codebase available to study or adjust model architecture, training, or inner workings."}, "llmdata": {"class": "closed", "link": "https://docs.cohere.com/docs/data-statement", "notes": "No documentation, listing or audit of pre-training data available. Cohere itself identifies it as coheretext-filtered and gives the size as 200Gb."}, "llmweights": {"class": "closed", "link": null, "notes": "No checkpoint or model prior to SFT and instruction-tuning made available"}, "rldata": {"class": "open", "link": "https://huggingface.co/collections/CohereForAI/aya-datasets-660415741bd4852f01c81c77", "notes": "Aya Collection (Aya Open Science initiative) is a multilingual collection of 513 million instances of promts and completions including instruction-style templates."}, "rlweights": {"class": "open", "link": "https://huggingface.co/CohereForAI/c4ai-command-r-v01/tree/main", "notes": "Fine-tuned model weights made available for download"}, "license": {"class": "partial", "link": "https://docs.cohere.com/docs/c4ai-acceptable-use-policy", "notes": "Licensed under CC-BY-NC and requires agreeing to C4AI acceptable use policy"}, "code": {"class": "closed", "link": null, "notes": "No source code available, so no documentation of code."}, "architecture": {"class": "closed", "link": null, "notes": "Architecture only sparsely documented."}, "preprint": {"class": "closed", "link": null, "notes": "No preprint appears to be made available at this time."}, "paper": {"class": "closed", "link": null, "notes": "No paper known to document the Cohere Command R+ model or architecture."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/CohereForAI/c4ai-command-r-v01-4bit", "notes": "Model card on HF document some aspects but provides no data on training data, instruction-tuning methods"}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not available."}, "package": {"class": "closed", "link": null, "notes": "No separate package available."}, "api": {"class": "closed", "link": null, "notes": "API access available only when signing up."}}

field_llmdata_notes:
No documentation, listing or audit of pre-training data available. Cohere itself identifies it as coheretext-filtered and gives the size as 200Gb.

field_rldata_notes:
Aya Collection (Aya Open Science initiative) is a multilingual collection of 513 million instances of promts and completions including instruction-style templates.

field_modelcard_notes:
Model card on HF document some aspects but provides no data on training data, instruction-tuning methods


id: orca_2
git_filename: projects/orca_2.yaml
format: yaml
field_project_name: Orca 2
field_project_link: https://www.microsoft.com/en-us/research/project/orca/
field_project_notes: This file applies to Orca 2 7B and 13B, both fine-tunes of corresponding Llama2 base models.
field_project_llmbase: LLaMA2
field_project_rlbase: FLAN, Math, undisclosed (synthetic)
field_project_license: Microsoft Research License, Llama Community License
field_org_name: Microsoft Research
field_org_link: https://www.microsoft.com/en-us/research/project/orca/
field_opencode_class: closed
field_opencode_notes: No source code made available anywhere for data curation, training, fine-tuning, or evaluation
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/microsoft/Orca-2-7b
field_rlweights_notes: 7B and 13B finetunes of Llama2 made available through HuggingFace
field_license_class: closed
field_license_link: https://github.com/facebookresearch/llama/blob/main/LICENSE
field_code_class: closed
field_code_notes: Code only covers minimal examples; no documentation available.
field_architecture_class: partial
field_architecture_link: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
field_architecture_notes: Architecture sketched in corporate preprints, though many details missing.
field_preprint_class: partial
field_preprint_link: https://arxiv.org/pdf/2311.11045.pdf
field_paper_class: closed
field_paper_notes: No peer-reviewed paper found
data:
{"project": {"name": "Orca 2", "link": "https://www.microsoft.com/en-us/research/project/orca/", "notes": "This file applies to Orca 2 7B and 13B, both fine-tunes of corresponding Llama2 base models.", "llmbase": "LLaMA2", "rlbase": "FLAN, Math, undisclosed (synthetic)", "license": "Microsoft Research License, Llama Community License"}, "org": {"name": "Microsoft Research", "link": "https://www.microsoft.com/en-us/research/project/orca/", "notes": null}, "opencode": {"class": "closed", "link": null, "notes": "No source code made available anywhere for data curation, training, fine-tuning, or evaluation"}, "llmdata": {"class": "closed", "link": null, "notes": "Llama pretraining Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "Instruction-tuning and explanation-tuning data described in preprint, but not disclosed or made available"}, "rlweights": {"class": "open", "link": "https://huggingface.co/microsoft/Orca-2-7b", "notes": "7B and 13B finetunes of Llama2 made available through HuggingFace"}, "license": {"class": "closed", "link": "https://github.com/facebookresearch/llama/blob/main/LICENSE", "notes": "Licensed under Microsoft Research License and Meta's bespoke community license, neither OSI recognised"}, "code": {"class": "closed", "link": null, "notes": "Code only covers minimal examples; no documentation available."}, "architecture": {"class": "partial", "link": "https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/", "notes": "Architecture sketched in corporate preprints, though many details missing."}, "preprint": {"class": "partial", "link": "https://arxiv.org/pdf/2311.11045.pdf", "notes": "Corporate preprint from Microsoft Research has some detail on instruction-tuning, explanation-tuning and evaluation"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/microsoft/Orca-2-7b", "notes": "Model card serves as landing page more than careful model documentation"}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "Model too large to load on HuggingFace inference library"}}

field_llmdata_notes:
Llama pretraining Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_rldata_notes:
Instruction-tuning and explanation-tuning data described in preprint, but not disclosed or made available

field_license_notes:
Licensed under Microsoft Research License and Meta's bespoke community license, neither OSI recognised

field_preprint_notes:
Corporate preprint from Microsoft Research has some detail on instruction-tuning, explanation-tuning and evaluation


id: OpenChat
git_filename: projects/OpenChat.yaml
format: yaml
field_project_name: OpenChat 3.5 7B
field_project_link: https://github.com/imoneoi/openchat
field_project_llmbase: Mistral 7B
field_project_rlbase: ShareGPT with C-RLFT
field_project_license: Apache 2.0
field_org_name: Tshinghua University
field_org_link: https://github.com/imoneoi
field_org_notes: OpenChat notes 'We are a student team from Tsinghua University'
field_opencode_class: open
field_opencode_link: https://github.com/imoneoi/openchat/tree/master/ochat
field_opencode_notes: Repository offers a large amount of fairly well-organized code for data curation and model
field_llmdata_class: closed
field_llmdata_notes: Pretraining data for Mistral is nowhere disclosed or documented
field_llmweights_class: open
field_llmweights_link: https://github.com/mistralai/mistral-src#download-the-model
field_llmweights_notes: Mistral 7B weights available via Mistral repository
field_rldata_class: closed
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/openchat/openchat_3.5/tree/main
field_rlweights_notes: Instruction-tuned model weights made available via HuggingFace
field_license_class: open
field_license_link: https://github.com/imoneoi/openchat/blob/master/LICENSE
field_license_notes: Code and model released under Apache 2.0
field_code_class: partial
field_code_link: https://github.com/imoneoi/openchat/tree/master/ochat
field_code_notes: There is plenty of code in the github repository but only some of it is documented
field_architecture_class: open
field_architecture_link: https://arxiv.org/abs/2309.11235
field_architecture_notes: Architecture quite well described in preprint
data:
{"project": {"name": "OpenChat 3.5 7B", "link": "https://github.com/imoneoi/openchat", "notes": null, "llmbase": "Mistral 7B", "rlbase": "ShareGPT with C-RLFT", "license": "Apache 2.0"}, "org": {"name": "Tshinghua University", "link": "https://github.com/imoneoi", "notes": "OpenChat notes 'We are a student team from Tsinghua University'"}, "opencode": {"class": "open", "link": "https://github.com/imoneoi/openchat/tree/master/ochat", "notes": "Repository offers a large amount of fairly well-organized code for data curation and model"}, "llmdata": {"class": "closed", "link": null, "notes": "Pretraining data for Mistral is nowhere disclosed or documented"}, "llmweights": {"class": "open", "link": "https://github.com/mistralai/mistral-src#download-the-model", "notes": "Mistral 7B weights available via Mistral repository"}, "rldata": {"class": "closed", "link": null, "notes": "Preprint says shareGPT dataset 'collected from sharegpt.com' but not disclosed or made available by this project"}, "rlweights": {"class": "open", "link": "https://huggingface.co/openchat/openchat_3.5/tree/main", "notes": "Instruction-tuned model weights made available via HuggingFace"}, "license": {"class": "open", "link": "https://github.com/imoneoi/openchat/blob/master/LICENSE", "notes": "Code and model released under Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/imoneoi/openchat/tree/master/ochat", "notes": "There is plenty of code in the github repository but only some of it is documented"}, "architecture": {"class": "open", "link": "https://arxiv.org/abs/2309.11235", "notes": "Architecture quite well described in preprint"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2309.11235", "notes": "Preprint describes the model architecture and instruction tuning approach, though is hampered by building on notoriously closed Llama2"}, "paper": {"class": "open", "link": "https://openreview.net/forum?id=AOJyfhWYHf", "notes": "Paper reviewed and accepted for ICLR 2024"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/openchat/openchat_v3.2", "notes": "There is a model card that provides some details on architecture and evaluation"}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "open", "link": "https://github.com/imoneoi/openchat/tree/master#installation", "notes": "Python package 'ochat' provided through pip"}, "api": {"class": "partial", "link": null, "notes": "Model too large to load onto HuggingFace free inference API, so only available through Inference Endpoints or package"}}

field_rldata_notes:
Preprint says shareGPT dataset 'collected from sharegpt.com' but not disclosed or made available by this project

field_preprint_notes:
Preprint describes the model architecture and instruction tuning approach, though is hampered by building on notoriously closed Llama2

field_api_notes:
Model too large to load onto HuggingFace free inference API, so only available through Inference Endpoints or package


id: pythia-chat-base-7B
git_filename: projects/pythia-chat-base-7B.yaml
format: yaml
field_project_name: Pythia-Chat-Base-7B-v0.16
field_project_link: https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B
field_project_llmbase: EleutherAI pythia
field_project_rlbase: OIG
field_project_license: Apache 2.0 license
field_org_name: togethercomputer
field_org_link: https://github.com/togethercomputer
field_opencode_class: open
field_llmdata_class: open
field_llmdata_link: https://github.com/togethercomputer/OpenDataHub
field_llmdata_notes: Training data curated and shared in separate repository
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B/tree/main
field_llmweights_notes: Model weights available via HuggingFace
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/laion/OIG
field_rlweights_class: closed
field_rlweights_notes: RL weights not separately made available
field_license_class: open
field_license_link: https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B#model-details
field_license_notes: Apache 2.0
field_code_class: open
field_code_link: https://github.com/togethercomputer/OpenChatKit
field_code_notes: Actively maintained repository
field_architecture_class: open
field_architecture_link: https://github.com/togethercomputer/OpenChatKit#reproducing-pythia-chat-base-7b
field_architecture_notes: Architecture and recipe for reproducing model provided
field_preprint_class: partial
field_preprint_link: https://arxiv.org/abs/2304.01373
data:
{"project": {"name": "Pythia-Chat-Base-7B-v0.16", "link": "https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B", "notes": null, "llmbase": "EleutherAI pythia", "rlbase": "OIG", "license": "Apache 2.0 license"}, "org": {"name": "togethercomputer", "link": "https://github.com/togethercomputer", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "open", "link": "https://github.com/togethercomputer/OpenDataHub", "notes": "Training data curated and shared in separate repository"}, "llmweights": {"class": "open", "link": "https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B/tree/main", "notes": "Model weights available via HuggingFace"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/laion/OIG", "notes": "From the documentation 'This is our attempt to create a large instruction dataset of medium quality along with a smaller high quality instruciton dataset (OIG-small-chip2).'"}, "rlweights": {"class": "closed", "link": null, "notes": "RL weights not separately made available"}, "license": {"class": "open", "link": "https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B#model-details", "notes": "Apache 2.0"}, "code": {"class": "open", "link": "https://github.com/togethercomputer/OpenChatKit", "notes": "Actively maintained repository"}, "architecture": {"class": "open", "link": "https://github.com/togethercomputer/OpenChatKit#reproducing-pythia-chat-base-7b", "notes": "Architecture and recipe for reproducing model provided"}, "preprint": {"class": "partial", "link": "https://arxiv.org/abs/2304.01373", "notes": "Preprint describes LM base (Pythia) but not instruction tuning details"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper or data audit found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/togethercomputer/Pythia-Chat-Base-7B", "notes": "Model card partially available but fairly minimally specified"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/laion/OIG", "notes": "OIG instruction dataset documented"}, "package": {"class": "open", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}

field_rldata_notes:
From the documentation 'This is our attempt to create a large instruction dataset of medium quality along with a smaller high quality instruciton dataset (OIG-small-chip2).'


id: minChatGPT
git_filename: projects/minChatGPT.yaml
format: yaml
field_project_name: minChatGPT
field_project_link: hhttps://github.com/ethanyanjiali/minChatGPT
field_project_llmbase: GPT2
field_project_rlbase: anthropic
field_project_license: GNU General Public License v3.0
field_org_name: ethanyanjiali
field_org_link: https://github.com/ethanyanjiali/minChatGPT
field_opencode_class: open
field_llmdata_class: open
field_llmweights_class: open
field_rldata_class: partial
field_rlweights_class: closed
field_license_class: open
field_code_class: open
field_architecture_class: partial
field_preprint_class: closed
field_paper_class: closed
field_modelcard_class: closed
field_datasheet_class: closed
field_package_class: closed
field_api_class: open
data:
{"project": {"name": "minChatGPT", "link": "hhttps://github.com/ethanyanjiali/minChatGPT", "notes": null, "llmbase": "GPT2", "rlbase": "anthropic", "license": "GNU General Public License v3.0"}, "org": {"name": "ethanyanjiali", "link": "https://github.com/ethanyanjiali/minChatGPT", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "open", "link": null, "notes": null}, "llmweights": {"class": "open", "link": null, "notes": null}, "rldata": {"class": "partial", "link": null, "notes": null}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": null}, "code": {"class": "open", "link": null, "notes": null}, "architecture": {"class": "partial", "link": null, "notes": null}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "closed", "link": null, "notes": null}, "api": {"class": "open", "link": null, "notes": null}}


id: olmo-7b-instruct
git_filename: projects/olmo-7b-instruct.yaml
format: yaml
field_project_name: OLMo 7B Instruct
field_project_link: https://blog.allenai.org/olmo-open-language-model-87ccfc95f580
field_project_llmbase: OLMo 7B
field_project_rlbase: OpenInstruct
field_project_license: Apache 2.0
field_org_name: Ai2
field_org_link: https://allenai.org
field_org_notes: Allen Institute for AI (non-profit research institute)
field_opencode_class: open
field_opencode_link: https://github.com/allenai/OLMo
field_opencode_notes: Multiple repos with training, architecture and fine-tuning code available
field_llmdata_class: open
field_llmdata_link: https://huggingface.co/datasets/allenai/dolma
field_llmdata_notes: Dolma training data released and documented in exemplary way
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/collections/allenai/olmo-suite-65aeaae8fe5b6b2122b46778
field_llmweights_notes: OLMo 7B and many training checkpoints available
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/allenai/ultrafeedback_binarized_cleaned
field_rldata_notes: Instruction tuning datasets documented and made available in exemplary ways
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/allenai/OLMo-7B-Instruct/tree/main
field_rlweights_notes: Full model weights made available
field_license_class: open
field_license_link: https://huggingface.co/allenai/OLMo-7B-Instruct
field_license_notes: Apache 2.0
field_code_class: open
field_code_link: https://huggingface.co/allenai/OLMo-7B-Instruct#model-sources
field_code_notes: repositories and code well-described, commented and documented
data:
{"project": {"name": "OLMo 7B Instruct", "link": "https://blog.allenai.org/olmo-open-language-model-87ccfc95f580", "notes": null, "llmbase": "OLMo 7B", "rlbase": "OpenInstruct", "license": "Apache 2.0"}, "org": {"name": "Ai2", "link": "https://allenai.org", "notes": "Allen Institute for AI (non-profit research institute)"}, "opencode": {"class": "open", "link": "https://github.com/allenai/OLMo", "notes": "Multiple repos with training, architecture and fine-tuning code available"}, "llmdata": {"class": "open", "link": "https://huggingface.co/datasets/allenai/dolma", "notes": "Dolma training data released and documented in exemplary way"}, "llmweights": {"class": "open", "link": "https://huggingface.co/collections/allenai/olmo-suite-65aeaae8fe5b6b2122b46778", "notes": "OLMo 7B and many training checkpoints available"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/allenai/ultrafeedback_binarized_cleaned", "notes": "Instruction tuning datasets documented and made available in exemplary ways"}, "rlweights": {"class": "open", "link": "https://huggingface.co/allenai/OLMo-7B-Instruct/tree/main", "notes": "Full model weights made available"}, "license": {"class": "open", "link": "https://huggingface.co/allenai/OLMo-7B-Instruct", "notes": "Apache 2.0"}, "code": {"class": "open", "link": "https://huggingface.co/allenai/OLMo-7B-Instruct#model-sources", "notes": "repositories and code well-described, commented and documented"}, "architecture": {"class": "open", "link": "https://huggingface.co/allenai/OLMo-7B-Instruct#model-sources", "notes": "Architectured documented in detail in model card, preprint, and technical blog posts"}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2402.00838", "notes": "Preprint describes model architecture, training and fine-tuning data, and training and SFT pipelines"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "open", "link": "https://huggingface.co/allenai/OLMo-7B-Instruct", "notes": "Model card provides broad overview and links to full details"}, "datasheet": {"class": "open", "link": "https://huggingface.co/datasets/allenai/dolma", "notes": "Data sheets and documentation available for the datasets used, linked here is Dolma"}, "package": {"class": "open", "link": "https://pypi.org/project/ai2-olmo/", "notes": "AI2-olmo available on PyPi"}, "api": {"class": "partial", "link": "https://huggingface.co/allenai/OLMo-7B-hf", "notes": "Available through HuggingFace though model is too large to run on free inference API"}}

field_preprint_notes:
Preprint describes model architecture, training and fine-tuning data, and training and SFT pipelines


id: trlx
git_filename: projects/trlx.yaml
format: yaml
field_project_name: trlx
field_project_link: https://github.com/CarperAI/trlx
field_project_llmbase: various (pythia, flan, OPT)
field_project_rlbase: various
field_project_license: MIT license
field_org_name: carperai
field_org_link: https://github.com/CarperAI/trlx
field_opencode_class: open
field_llmdata_class: open
field_llmweights_class: open
field_rldata_class: partial
field_rlweights_class: closed
field_license_class: open
field_code_class: open
field_architecture_class: partial
field_preprint_class: closed
field_paper_class: closed
field_modelcard_class: closed
field_datasheet_class: closed
field_package_class: partial
field_api_class: open
data:
{"project": {"name": "trlx", "link": "https://github.com/CarperAI/trlx", "notes": null, "llmbase": "various (pythia, flan, OPT)", "rlbase": "various", "license": "MIT license"}, "org": {"name": "carperai", "link": "https://github.com/CarperAI/trlx", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "open", "link": null, "notes": null}, "llmweights": {"class": "open", "link": null, "notes": null}, "rldata": {"class": "partial", "link": null, "notes": null}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": null}, "code": {"class": "open", "link": null, "notes": null}, "architecture": {"class": "partial", "link": null, "notes": null}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "closed", "link": null, "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "partial", "link": null, "notes": null}, "api": {"class": "open", "link": null, "notes": null}}


id: MPT-30b-instruct
git_filename: projects/MPT-30b-instruct.yaml
format: yaml
field_project_name: MPT-30B Instruct
field_project_link: https://huggingface.co/mosaicml/mpt-30b-instruct
field_project_llmbase: MosaicML
field_project_rlbase: dolly, anthropic
field_project_license: CC-By-SA-3.0
field_org_name: MosaicML
field_org_link: https://www.mosaicml.com
field_opencode_class: open
field_opencode_link: https://github.com/mosaicml/llm-foundry/tree/main/llmfoundry/models/mpt
field_opencode_notes: Codebase part of LLM foundry
field_llmdata_class: partial
field_llmdata_link: https://huggingface.co/datasets/c4
field_llmdata_notes: C4 is part of the dataset but a precise specification of source data is hard to find
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/mosaicml/mpt-30b-instruct/tree/main
field_llmweights_notes: Weights available via HuggingFace
field_rldata_class: partial
field_rldata_link: https://huggingface.co/datasets/mosaicml/dolly_hhrlhf
field_rldata_notes: dolly-hhrlhf, combination of Databrick dolly-15k dataset and a filtered subset of Anthropic HH-RLHF
field_rlweights_class: closed
field_license_class: open
field_license_notes: CC-by-SA 3.0
field_code_class: open
field_code_link: https://github.com/mosaicml/llm-foundry/
field_code_notes: LLM Foundry codebase is well-documented and in active development.
field_architecture_class: partial
field_architecture_link: https://huggingface.co/mosaicml/mpt-30b-instruct
field_architecture_notes: Architecture reasonably well-documented
field_preprint_class: closed
data:
{"project": {"name": "MPT-30B Instruct", "link": "https://huggingface.co/mosaicml/mpt-30b-instruct", "notes": null, "llmbase": "MosaicML", "rlbase": "dolly, anthropic", "license": "CC-By-SA-3.0"}, "org": {"name": "MosaicML", "link": "https://www.mosaicml.com", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/mosaicml/llm-foundry/tree/main/llmfoundry/models/mpt", "notes": "Codebase part of LLM foundry"}, "llmdata": {"class": "partial", "link": "https://huggingface.co/datasets/c4", "notes": "C4 is part of the dataset but a precise specification of source data is hard to find"}, "llmweights": {"class": "open", "link": "https://huggingface.co/mosaicml/mpt-30b-instruct/tree/main", "notes": "Weights available via HuggingFace"}, "rldata": {"class": "partial", "link": "https://huggingface.co/datasets/mosaicml/dolly_hhrlhf", "notes": "dolly-hhrlhf, combination of Databrick dolly-15k dataset and a filtered subset of Anthropic HH-RLHF"}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": "CC-by-SA 3.0"}, "code": {"class": "open", "link": "https://github.com/mosaicml/llm-foundry/", "notes": "LLM Foundry codebase is well-documented and in active development."}, "architecture": {"class": "partial", "link": "https://huggingface.co/mosaicml/mpt-30b-instruct", "notes": "Architecture reasonably well-documented"}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "partial", "link": "https://huggingface.co/mosaicml/mpt-30b-instruct", "notes": "Modelcard is somewhat lacking in detail"}, "datasheet": {"class": "closed", "link": "https://www.mosaicml.com/blog/mpt-30b", "notes": "Datasheet not available; data somewhat documented in blog post at link"}, "package": {"class": "open", "link": null, "notes": null}, "api": {"class": "partial", "link": null, "notes": "API via HuggingFace"}}


id: mistral-7B
git_filename: projects/mistral-7B.yaml
format: yaml
field_project_name: Mistral 7B-Instruct
field_project_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1
field_project_llmbase: unclear
field_project_rlbase: unspecified
field_project_license: Apache 2.0
field_org_name: Mistral AI
field_org_link: https://mistral.ai/
field_opencode_class: partial
field_opencode_link: https://github.com/mistralai/mistral-src
field_opencode_notes: repository provides 'minimal code to run our 7B model'
field_llmdata_class: closed
field_llmdata_notes: No information provided on pretraining data
field_llmweights_class: open
field_llmweights_link: https://github.com/mistralai/mistral-src#download-the-model
field_llmweights_notes: Base LLM model made available for download
field_rldata_class: closed
field_rldata_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/tree/main
field_rlweights_notes: Instruct version of the model made available but no information on fine-tuning procedure provided
field_license_class: open
field_license_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/blob/main/README.md
field_license_notes: Apache 2.0
field_code_class: closed
field_code_link: https://github.com/mistralai/mistral-src
field_code_notes: the little code that is available is uncommented and undocumented
field_architecture_class: partial
field_architecture_link: https://github.com/mistralai/mistral-src
field_architecture_notes: Some information on architecture provided in github repo
data:
{"project": {"name": "Mistral 7B-Instruct", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1", "notes": null, "llmbase": "unclear", "rlbase": "unspecified", "license": "Apache 2.0"}, "org": {"name": "Mistral AI", "link": "https://mistral.ai/", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/mistralai/mistral-src", "notes": "repository provides 'minimal code to run our 7B model'"}, "llmdata": {"class": "closed", "link": null, "notes": "No information provided on pretraining data"}, "llmweights": {"class": "open", "link": "https://github.com/mistralai/mistral-src#download-the-model", "notes": "Base LLM model made available for download"}, "rldata": {"class": "closed", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1", "notes": "No information provided expect that instruction tuning is done using an unspecified 'variety of publicly available conversation datasets'"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/tree/main", "notes": "Instruct version of the model made available but no information on fine-tuning procedure provided"}, "license": {"class": "open", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/blob/main/README.md", "notes": "Apache 2.0"}, "code": {"class": "closed", "link": "https://github.com/mistralai/mistral-src", "notes": "the little code that is available is uncommented and undocumented"}, "architecture": {"class": "partial", "link": "https://github.com/mistralai/mistral-src", "notes": "Some information on architecture provided in github repo"}, "preprint": {"class": "partial", "link": "http://arxiv.org/abs/2310.06825", "notes": "Preprint rehashes marketing blurbs also given in blog and provides no details about pretraining datasets, instruction tuning datasets, or fine-tuning process, hence partial."}, "paper": {"class": "closed", "link": null, "notes": "No peer reviewed paper available"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card available, HuggingFace modelcard just points to a corporate blog post"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet available"}, "package": {"class": "partial", "link": "https://docs.mistral.ai/quickstart/", "notes": "Docker image shared on github"}, "api": {"class": "open", "link": "https://docs.mistral.ai/api", "notes": "API specification provided by vLLM"}}

field_rldata_notes:
No information provided expect that instruction tuning is done using an unspecified 'variety of publicly available conversation datasets'

field_preprint_notes:
Preprint rehashes marketing blurbs also given in blog and provides no details about pretraining datasets, instruction tuning datasets, or fine-tuning process, hence partial.


id: llama-3-instruct
git_filename: projects/llama-3-instruct.yaml
format: yaml
field_project_name: Llama 3 Instruct
field_project_link: https://huggingface.co/collections/meta-llama/meta-llama-3-66214712577ca38149ebb2b6
field_project_llmbase: Meta Llama 3
field_project_rlbase: Meta, undocumented
field_project_license: Meta Llama 3 Community License
field_org_name: Facebook Research
field_org_link: https://github.com/facebookresearch
field_opencode_class: closed
field_opencode_link: https://github.com/meta-llama/llama3
field_opencode_notes: Repository only offers minimal code
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rldata_notes: No information available on instruction-tuning.
field_rlweights_class: partial
field_rlweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_rlweights_notes: Download only after requesting access; requires signing a consent form
field_license_class: closed
field_license_link: https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct/tree/main
field_code_class: closed
field_code_notes: Code only covers minimal examples; no documentation available.
field_architecture_class: partial
field_architecture_link: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
field_architecture_notes: Architecture sketched in glossy blog post.
field_preprint_class: closed
field_preprint_notes: No preprint or any other scientific documentation available.
field_paper_class: closed
data:
{"project": {"name": "Llama 3 Instruct", "link": "https://huggingface.co/collections/meta-llama/meta-llama-3-66214712577ca38149ebb2b6", "notes": null, "llmbase": "Meta Llama 3", "rlbase": "Meta, undocumented", "license": "Meta Llama 3 Community License"}, "org": {"name": "Facebook Research", "link": "https://github.com/facebookresearch", "notes": null}, "opencode": {"class": "closed", "link": "https://github.com/meta-llama/llama3", "notes": "Repository only offers minimal code"}, "llmdata": {"class": "closed", "link": null, "notes": "Data nowhere disclosed or documented, and described only in the vaguest terms in a release blog post"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "No information available on instruction-tuning."}, "rlweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "license": {"class": "closed", "link": "https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct/tree/main", "notes": "Even inspecting the model requires signing Meta Llama 3's bespoke 'community license', not an OSI recognised open license"}, "code": {"class": "closed", "link": null, "notes": "Code only covers minimal examples; no documentation available."}, "architecture": {"class": "partial", "link": "https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/", "notes": "Architecture sketched in glossy blog post."}, "preprint": {"class": "closed", "link": null, "notes": "No preprint or any other scientific documentation available."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper available."}, "modelcard": {"class": "partial", "link": "https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md", "notes": "There is a model card, but it provides the absolute minimum of detail, and none whatsoever on training data."}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "API only available behind a privacy-defying signup form"}}

field_llmdata_notes:
Data nowhere disclosed or documented, and described only in the vaguest terms in a release blog post

field_license_notes:
Even inspecting the model requires signing Meta Llama 3's bespoke 'community license', not an OSI recognised open license

field_modelcard_notes:
There is a model card, but it provides the absolute minimum of detail, and none whatsoever on training data.


id: ultraLM
git_filename: projects/ultraLM.yaml
format: yaml
field_project_name: UltraLM
field_project_link: https://huggingface.co/openbmb/UltraRM-13b
field_project_llmbase: LLaMA2
field_project_rlbase: UltraFeedback (part synthetic)
field_project_license: Meta Community License
field_org_name: OpenBMB
field_org_link: https://www.openbmb.org/
field_opencode_class: closed
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/openbmb/UltraFeedback
field_rldata_notes: UltraFeedback dataset made available along with model release
field_rlweights_class: partial
field_rlweights_link: https://huggingface.co/openbmb/UltraLM-13b-v2.0
field_license_class: closed
field_license_link: https://huggingface.co/openbmb/UltraLM-13b#model-details
field_license_notes: Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license
field_code_class: closed
field_code_notes: Code only covers minimal examples; no documentation available.
field_architecture_class: partial
field_architecture_link: https://huggingface.co/openbmb/UltraLM-13b#model-details
field_architecture_notes: Architecture sketched in online materials.
field_preprint_class: open
field_preprint_link: https://arxiv.org/abs/2310.01377
field_paper_class: closed
field_paper_notes: No peer-reviewed paper found
data:
{"project": {"name": "UltraLM", "link": "https://huggingface.co/openbmb/UltraRM-13b", "notes": null, "llmbase": "LLaMA2", "rlbase": "UltraFeedback (part synthetic)", "license": "Meta Community License"}, "org": {"name": "OpenBMB", "link": "https://www.openbmb.org/", "notes": "OpenBMB (Open Lab for Big Model Base), founded by TsinghuaNLP & ModelBest Inc (\u9762\u58c1\u667a\u80fd), aims to build foundation models and systems towards AGI."}, "opencode": {"class": "closed", "link": null, "notes": null}, "llmdata": {"class": "closed", "link": null, "notes": "Based on Llama2, which means pretraining data is nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/openbmb/UltraFeedback", "notes": "UltraFeedback dataset made available along with model release"}, "rlweights": {"class": "partial", "link": "https://huggingface.co/openbmb/UltraLM-13b-v2.0", "notes": "Online materials appear to be in flux and several HuggingFace links generate 404 errors, hence partial"}, "license": {"class": "closed", "link": "https://huggingface.co/openbmb/UltraLM-13b#model-details", "notes": "Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license"}, "code": {"class": "closed", "link": null, "notes": "Code only covers minimal examples; no documentation available."}, "architecture": {"class": "partial", "link": "https://huggingface.co/openbmb/UltraLM-13b#model-details", "notes": "Architecture sketched in online materials."}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2310.01377", "notes": "Preprint describes creation of UltraFeedback dataset but also offers some detail on training and architecture of UltraRM models"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/openbmb/UltraLM-13b#model-details", "notes": "Model card on HuggingFace available for 13b (Llama1) model, but not for newer releases, hence partial"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/openbmb/UltraFeedback", "notes": "Datasheet available for RLHF portion, but not for Llama2-based pretraining data, hence partial"}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "closed", "link": null, "notes": "API not provided and model too big for HuggingFace inference API"}}

field_org_notes:
OpenBMB (Open Lab for Big Model Base), founded by TsinghuaNLP & ModelBest Inc (面壁智能), aims to build foundation models and systems towards AGI.

field_llmdata_notes:
Based on Llama2, which means pretraining data is nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_rlweights_notes:
Online materials appear to be in flux and several HuggingFace links generate 404 errors, hence partial

field_preprint_notes:
Preprint describes creation of UltraFeedback dataset but also offers some detail on training and architecture of UltraRM models

field_modelcard_notes:
Model card on HuggingFace available for 13b (Llama1) model, but not for newer releases, hence partial


id: neuralchat-7b
git_filename: projects/neuralchat-7b.yaml
format: yaml
field_project_name: NeuralChat 7B
field_project_link: https://huggingface.co/Intel/neural-chat-7b-v3-1
field_project_notes: A mistral-based Orca-finetuned chat model
field_project_llmbase: Mistral 7B
field_project_rlbase: Orca
field_project_license: Apache 2.0
field_org_name: Intel
field_opencode_class: partial
field_opencode_notes: Mistral base model is not open, but repo gives sample code for fine-tuning based on that
field_llmdata_class: closed
field_llmdata_notes: Mistral has not disclosed anything about its training data
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/mistralai/Mistral-7B-v0.1
field_llmweights_notes: Based on Mistral 7B 0.1
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/Open-Orca/SlimOrca
field_rldata_notes: RL dataset used for post-training is shared and available
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/Intel/neural-chat-7b-v3-1/tree/main
field_rlweights_notes: finetuned model made openly available by Intel
field_license_class: open
field_license_link: https://huggingface.co/Intel/neural-chat-7b-v3-1/blob/main/LICENSE
field_license_notes: Apache 2.0
field_code_class: partial
field_architecture_class: partial
field_architecture_notes: Described in on HuggingFace model card and a Medium post
field_preprint_class: closed
field_preprint_notes: A medium post is apparently the only scientific documentation of this model
field_paper_class: closed
data:
{"project": {"name": "NeuralChat 7B", "link": "https://huggingface.co/Intel/neural-chat-7b-v3-1", "notes": "A mistral-based Orca-finetuned chat model", "llmbase": "Mistral 7B", "rlbase": "Orca", "license": "Apache 2.0"}, "org": {"name": "Intel", "link": "https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/NeuralChat-A-Customizable-Chatbot-Framework/post/1526789", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3", "notes": "Mistral base model is not open, but repo gives sample code for fine-tuning based on that"}, "llmdata": {"class": "closed", "link": null, "notes": "Mistral has not disclosed anything about its training data"}, "llmweights": {"class": "open", "link": "https://huggingface.co/mistralai/Mistral-7B-v0.1", "notes": "Based on Mistral 7B 0.1"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/Open-Orca/SlimOrca", "notes": "RL dataset used for post-training is shared and available"}, "rlweights": {"class": "open", "link": "https://huggingface.co/Intel/neural-chat-7b-v3-1/tree/main", "notes": "finetuned model made openly available by Intel"}, "license": {"class": "open", "link": "https://huggingface.co/Intel/neural-chat-7b-v3-1/blob/main/LICENSE", "notes": "Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3#how-to-train-intelneural-chat-7b-v3-1-on-intel-gaudi2", "notes": "Mistral remains closed so only documentation pertains to fine-tuning steps, but that code is quite well documented, so partial."}, "architecture": {"class": "partial", "link": "https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3", "notes": "Described in on HuggingFace model card and a Medium post"}, "preprint": {"class": "closed", "link": "https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3", "notes": "A medium post is apparently the only scientific documentation of this model"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://huggingface.co/Intel/neural-chat-7b-v3-1", "notes": "No model card for Mistral base model portion."}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/Open-Orca/OpenOrca", "notes": "SlimOrca dataset is described as part of OpenOrca (but partial since Mistral data is incrutable)"}, "package": {"class": "partial", "link": "https://huggingface.co/Intel/neural-chat-7b-v3-1#fp32-inference-with-transformers", "notes": "Code for running with transformers provided by Intel"}, "api": {"class": "closed", "link": null, "notes": "Provided through HuggingFace but model too large to run via inference API, local deployment or paid access needed"}}

field_org_link:
https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/NeuralChat-A-Customizable-Chatbot-Framework/post/1526789

field_opencode_link:
https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3

field_code_link:
https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3#how-to-train-intelneural-chat-7b-v3-1-on-intel-gaudi2

field_code_notes:
Mistral remains closed so only documentation pertains to fine-tuning steps, but that code is quite well documented, so partial.

field_architecture_link:
https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3

field_preprint_link:
https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3

field_api_notes:
Provided through HuggingFace but model too large to run via inference API, local deployment or paid access needed


id: RedPajama-INCITE-Instruct-7B
git_filename: projects/RedPajama-INCITE-Instruct-7B.yaml
format: yaml
field_project_name: RedPajama-INCITE-Instruct-7B
field_project_link: https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct
field_project_llmbase: RedPajama-INCITE-7B-Base
field_project_rlbase: various (GPT-JT recipe)
field_project_license: Apache 2.0
field_org_name: TogetherComputer
field_org_link: https://together.ai/
field_opencode_class: partial
field_opencode_link: https://github.com/togethercomputer/redpajama.cpp/tree/master/examples/redpajama
field_opencode_notes: Code for datasets made available in exemplary ways; code for training and tuning harder to find
field_llmdata_class: open
field_llmdata_link: https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T
field_llmdata_notes: RedPajama-Data-1T made available on HuggingFace
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Base
field_llmweights_notes: Base is RedPajama-INCITE-7B-Base
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/togethercomputer/RedPajama-Data-Instruct
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct
field_rlweights_notes: Instruction-tuned version made available in paralle with base version
field_license_class: partial
field_license_link: https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct/blob/main/README.md
field_code_class: partial
field_architecture_class: partial
field_architecture_link: https://together.ai/blog/redpajama
field_architecture_notes: Architecture detailed on model card, crucial parts appear to be forked from GPT-NeoX
field_preprint_class: closed
field_preprint_notes: No preprint found
data:
{"project": {"name": "RedPajama-INCITE-Instruct-7B", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct", "notes": null, "llmbase": "RedPajama-INCITE-7B-Base", "rlbase": "various (GPT-JT recipe)", "license": "Apache 2.0"}, "org": {"name": "TogetherComputer", "link": "https://together.ai/", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/togethercomputer/redpajama.cpp/tree/master/examples/redpajama", "notes": "Code for datasets made available in exemplary ways; code for training and tuning harder to find"}, "llmdata": {"class": "open", "link": "https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T", "notes": "RedPajama-Data-1T made available on HuggingFace"}, "llmweights": {"class": "open", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Base", "notes": "Base is RedPajama-INCITE-7B-Base"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/togethercomputer/RedPajama-Data-Instruct", "notes": "The model was trained on a large collection of diverse data, including Chain-of-Thought (CoT), Public Pool of Prompts (P3) dataset, Natural-Instructions (NI) dataset."}, "rlweights": {"class": "open", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct", "notes": "Instruction-tuned version made available in paralle with base version"}, "license": {"class": "partial", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct/blob/main/README.md", "notes": "Models licensed under Apache 2.0, but note that the data itself is variably licensed and so imposes some limitations."}, "code": {"class": "partial", "link": null, "notes": "Code for base LLM and instruction tuning datasets beautifully documented; code specifying training and fine-tuning sparsely documented."}, "architecture": {"class": "partial", "link": "https://together.ai/blog/redpajama", "notes": "Architecture detailed on model card, crucial parts appear to be forked from GPT-NeoX"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found"}, "paper": {"class": "closed", "link": null, "notes": "No paper found"}, "modelcard": {"class": "open", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct", "notes": "Model card and readme provide details on datasets and"}, "datasheet": {"class": "open", "link": "https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T", "notes": "Data sheet includes links to data and recipes to create from scratch"}, "package": {"class": "closed", "link": null, "notes": "No separate package found"}, "api": {"class": "partial", "link": "https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct", "notes": "Hosted inference API available through HuggingFace"}}

field_rldata_notes:
The model was trained on a large collection of diverse data, including Chain-of-Thought (CoT), Public Pool of Prompts (P3) dataset, Natural-Instructions (NI) dataset.

field_license_notes:
Models licensed under Apache 2.0, but note that the data itself is variably licensed and so imposes some limitations.

field_code_notes:
Code for base LLM and instruction tuning datasets beautifully documented; code specifying training and fine-tuning sparsely documented.


id: alpaca
git_filename: projects/alpaca.yaml
format: yaml
field_project_name: Stanford Alpaca
field_project_link: https://crfm.stanford.edu/2023/03/13/alpaca.html
field_project_notes: project_notes
field_project_llmbase: LLaMA
field_project_rlbase: Self-Instruct (synthetic)
field_project_license: LLaMA license agreement
field_org_name: Stanford University CRFM
field_org_link: https://crfm.stanford.edu/
field_opencode_class: open
field_llmdata_class: closed
field_llmdata_notes: Based on LLaMA, whose pretraining data is nowhere disclosed or documented.
field_llmweights_class: partial
field_llmweights_notes: LLaMA based, copyright status unclear
field_rldata_class: partial
field_rldata_link: https://github.com/tatsu-lab/stanford_alpaca#data-release
field_rldata_notes: alpaca_data.json contains 52K instruction-following data we used for fine-tuning the Alpaca model.
field_rlweights_class: partial
field_rlweights_link: https://github.com/tatsu-lab/stanford_alpaca#data-release
field_rlweights_notes: LLaMA based
field_license_class: closed
field_license_link: https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform
field_license_notes: Pegged to LLaMA licence agreement
field_code_class: partial
field_code_link: https://github.com/tatsu-lab/stanford_alpaca
field_code_notes: Insofar as code is made available it is fairly well documented
field_architecture_class: open
field_architecture_link: https://github.com/tatsu-lab/stanford_alpaca#fine-tuning
field_architecture_notes: Fair bit of documentation available on github repository
field_preprint_class: closed
data:
{"project": {"name": "Stanford Alpaca", "link": "https://crfm.stanford.edu/2023/03/13/alpaca.html", "notes": "project_notes", "llmbase": "LLaMA", "rlbase": "Self-Instruct (synthetic)", "license": "LLaMA license agreement"}, "org": {"name": "Stanford University CRFM", "link": "https://crfm.stanford.edu/", "notes": null}, "opencode": {"class": "open", "link": null, "notes": null}, "llmdata": {"class": "closed", "link": null, "notes": "Based on LLaMA, whose pretraining data is nowhere disclosed or documented."}, "llmweights": {"class": "partial", "link": null, "notes": "LLaMA based, copyright status unclear"}, "rldata": {"class": "partial", "link": "https://github.com/tatsu-lab/stanford_alpaca#data-release", "notes": "alpaca_data.json contains 52K instruction-following data we used for fine-tuning the Alpaca model."}, "rlweights": {"class": "partial", "link": "https://github.com/tatsu-lab/stanford_alpaca#data-release", "notes": "LLaMA based"}, "license": {"class": "closed", "link": "https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform", "notes": "Pegged to LLaMA licence agreement"}, "code": {"class": "partial", "link": "https://github.com/tatsu-lab/stanford_alpaca", "notes": "Insofar as code is made available it is fairly well documented"}, "architecture": {"class": "open", "link": "https://github.com/tatsu-lab/stanford_alpaca#fine-tuning", "notes": "Fair bit of documentation available on github repository"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found; uses the release-by-blogpost playbook"}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed work found."}, "modelcard": {"class": "closed", "link": null, "notes": "No model card found"}, "datasheet": {"class": "closed", "link": null, "notes": "No data sheet found"}, "package": {"class": "closed", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}


id: mistral-nemo
git_filename: projects/mistral-nemo.yaml
format: yaml
field_project_name: Mistral NeMo Instruct
field_project_link: https://mistral.ai/news/mistral-nemo/
field_project_llmbase: Mistral NeMo
field_project_rlbase: unspecified
field_project_license: Apache 2.0 (model weights only)
field_org_name: Mistral AI
field_org_link: https://mistral.ai/
field_opencode_class: partial
field_opencode_link: https://github.com/mistralai/mistral-inference
field_opencode_notes: repository provides 'minimal code to run our models'
field_llmdata_class: closed
field_llmdata_notes: No information provided on pretraining data
field_llmweights_class: open
field_llmweights_link: https://models.mistralcdn.com/mistral-nemo-2407/mistral-nemo-base-2407.tar
field_llmweights_notes: Base LLM model made available for download
field_rldata_class: closed
field_rldata_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1
field_rlweights_class: partial
field_rlweights_link: https://models.mistralcdn.com/mistral-nemo-2407/mistral-nemo-instruct-2407.tar
field_rlweights_notes: Instruct version of the model made available but no information on fine-tuning procedure provided
field_license_class: open
field_license_link: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/blob/main/README.md
field_license_notes: Apache 2.0
field_code_class: closed
field_code_link: https://github.com/mistralai/mistral-inference
field_code_notes: the little code that is available is uncommented and undocumented
field_architecture_class: partial
field_architecture_link: https://github.com/mistralai/mistral-inference
field_architecture_notes: Some information on architecture provided in github repo and in release blogpost
data:
{"project": {"name": "Mistral NeMo Instruct", "link": "https://mistral.ai/news/mistral-nemo/", "notes": null, "llmbase": "Mistral NeMo", "rlbase": "unspecified", "license": "Apache 2.0 (model weights only)"}, "org": {"name": "Mistral AI", "link": "https://mistral.ai/", "notes": null}, "opencode": {"class": "partial", "link": "https://github.com/mistralai/mistral-inference", "notes": "repository provides 'minimal code to run our models'"}, "llmdata": {"class": "closed", "link": null, "notes": "No information provided on pretraining data"}, "llmweights": {"class": "open", "link": "https://models.mistralcdn.com/mistral-nemo-2407/mistral-nemo-base-2407.tar", "notes": "Base LLM model made available for download"}, "rldata": {"class": "closed", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1", "notes": "No information provided expect that instruction tuning is done using an unspecified 'variety of publicly available conversation datasets'"}, "rlweights": {"class": "partial", "link": "https://models.mistralcdn.com/mistral-nemo-2407/mistral-nemo-instruct-2407.tar", "notes": "Instruct version of the model made available but no information on fine-tuning procedure provided"}, "license": {"class": "open", "link": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/blob/main/README.md", "notes": "Apache 2.0"}, "code": {"class": "closed", "link": "https://github.com/mistralai/mistral-inference", "notes": "the little code that is available is uncommented and undocumented"}, "architecture": {"class": "partial", "link": "https://github.com/mistralai/mistral-inference", "notes": "Some information on architecture provided in github repo and in release blogpost"}, "preprint": {"class": "closed", "link": null, "notes": "No preprint found"}, "paper": {"class": "closed", "link": null, "notes": "No peer reviewed paper available"}, "modelcard": {"class": "closed", "link": null, "notes": "No model card available"}, "datasheet": {"class": "closed", "link": null, "notes": "No datasheet available"}, "package": {"class": "partial", "link": "https://docs.mistral.ai/quickstart/", "notes": "Docker image shared on github"}, "api": {"class": "open", "link": "https://docs.mistral.ai/api", "notes": "API specification provided by vLLM"}}

field_rldata_notes:
No information provided expect that instruction tuning is done using an unspecified 'variety of publicly available conversation datasets'


id: llama-2-chat
git_filename: projects/llama-2-chat.yaml
format: yaml
field_project_name: LLaMA2 Chat
field_project_link: https://ai.meta.com/resources/models-and-libraries/llama/
field_project_llmbase: LLaMA2
field_project_rlbase: Meta, StackExchange, Anthropic
field_project_license: Unclear
field_org_name: Facebook Research
field_org_link: https://github.com/facebookresearch
field_opencode_class: closed
field_opencode_link: https://github.com/facebookresearch/llama/tree/main
field_llmdata_class: closed
field_llmweights_class: partial
field_llmweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_llmweights_notes: Download only after requesting access; requires signing a consent form
field_rldata_class: closed
field_rlweights_class: partial
field_rlweights_link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
field_rlweights_notes: Download only after requesting access; requires signing a consent form
field_license_class: closed
field_license_link: https://github.com/facebookresearch/llama/blob/main/LICENSE
field_license_notes: Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license
field_code_class: closed
field_code_notes: Code only covers minimal examples; no documentation available.
field_architecture_class: partial
field_architecture_link: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
field_architecture_notes: Architecture sketched in preprint, though many details missing.
field_preprint_class: partial
field_preprint_link: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
field_paper_class: closed
field_paper_notes: No peer-reviewed paper found
data:
{"project": {"name": "LLaMA2 Chat", "link": "https://ai.meta.com/resources/models-and-libraries/llama/", "notes": null, "llmbase": "LLaMA2", "rlbase": "Meta, StackExchange, Anthropic", "license": "Unclear"}, "org": {"name": "Facebook Research", "link": "https://github.com/facebookresearch", "notes": null}, "opencode": {"class": "closed", "link": "https://github.com/facebookresearch/llama/tree/main", "notes": "Repository only offers 'a minimal example to load Llama 2 models and run inference'; no training, fine-tuning, evaluation code made available"}, "llmdata": {"class": "closed", "link": null, "notes": "Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta"}, "llmweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "rldata": {"class": "closed", "link": null, "notes": "RLHF data including 1 million Meta-specific tuning prompts not made available (even as it incorporates some open RLHF datasets)"}, "rlweights": {"class": "partial", "link": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/", "notes": "Download only after requesting access; requires signing a consent form"}, "license": {"class": "closed", "link": "https://github.com/facebookresearch/llama/blob/main/LICENSE", "notes": "Usage requires signing Meta's bespoke 'community license', not an OSI recognised open license"}, "code": {"class": "closed", "link": null, "notes": "Code only covers minimal examples; no documentation available."}, "architecture": {"class": "partial", "link": "https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/", "notes": "Architecture sketched in preprint, though many details missing."}, "preprint": {"class": "partial", "link": "https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/", "notes": "Corporate preprint quite some detail on pretraining, RLHF, and safety measures but none on datasets."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper found"}, "modelcard": {"class": "partial", "link": "https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md", "notes": "There is a model card, but it provides the absolute minimum of detail, and none whatsoever on training data."}, "datasheet": {"class": "closed", "link": null, "notes": "Datasheet not provided."}, "package": {"class": "closed", "link": null, "notes": "Package not provided"}, "api": {"class": "partial", "link": null, "notes": "API only available behind a privacy-defying signup form"}}

field_opencode_notes:
Repository only offers 'a minimal example to load Llama 2 models and run inference'; no training, fine-tuning, evaluation code made available

field_llmdata_notes:
Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta

field_rldata_notes:
RLHF data including 1 million Meta-specific tuning prompts not made available (even as it incorporates some open RLHF datasets)

field_preprint_notes:
Corporate preprint quite some detail on pretraining, RLHF, and safety measures but none on datasets.

field_modelcard_notes:
There is a model card, but it provides the absolute minimum of detail, and none whatsoever on training data.


id: amber
git_filename: projects/amber.yaml
format: yaml
field_project_name: AmberChat
field_project_link: https://huggingface.co/LLM360/AmberChat
field_project_llmbase: Amber
field_project_rlbase: ShareGPT + Evol-Instruct (synthetic)
field_project_license: Apache 2.0
field_org_name: LLM360
field_org_link: https://www.llm360.ai/index.html
field_org_notes: LLM360, an initiative to fully open-source LLMs
field_opencode_class: open
field_opencode_link: https://github.com/LLM360/amber-train/tree/main
field_opencode_notes: amber-train repository includes code for training and finetuning.
field_llmdata_class: open
field_llmdata_link: https://huggingface.co/datasets/LLM360/AmberDatasets
field_llmdata_notes: data well-documented and openly available
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/LLM360/Amber
field_llmweights_notes: 360 model checkpoints released
field_rldata_class: open
field_rldata_link: https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k
field_rldata_notes: RL and fine-tuning data shared and documented
field_rlweights_class: open
field_rlweights_link: https://huggingface.co/LLM360/AmberChat
field_rlweights_notes: Finetuned model available for download.
field_license_class: open
field_license_link: https://huggingface.co/LLM360/AmberChat
field_license_notes: Everything licensed under Apache 2.0
field_code_class: partial
field_code_link: https://github.com/LLM360
field_code_notes: Code documented in helpful readme.md files but only partly inline.
data:
{"project": {"name": "AmberChat", "link": "https://huggingface.co/LLM360/AmberChat", "notes": null, "llmbase": "Amber", "rlbase": "ShareGPT + Evol-Instruct (synthetic)", "license": "Apache 2.0"}, "org": {"name": "LLM360", "link": "https://www.llm360.ai/index.html", "notes": "LLM360, an initiative to fully open-source LLMs"}, "opencode": {"class": "open", "link": "https://github.com/LLM360/amber-train/tree/main", "notes": "amber-train repository includes code for training and finetuning."}, "llmdata": {"class": "open", "link": "https://huggingface.co/datasets/LLM360/AmberDatasets", "notes": "data well-documented and openly available"}, "llmweights": {"class": "open", "link": "https://huggingface.co/LLM360/Amber", "notes": "360 model checkpoints released"}, "rldata": {"class": "open", "link": "https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k", "notes": "RL and fine-tuning data shared and documented"}, "rlweights": {"class": "open", "link": "https://huggingface.co/LLM360/AmberChat", "notes": "Finetuned model available for download."}, "license": {"class": "open", "link": "https://huggingface.co/LLM360/AmberChat", "notes": "Everything licensed under Apache 2.0"}, "code": {"class": "partial", "link": "https://github.com/LLM360", "notes": "Code documented in helpful readme.md files but only partly inline."}, "architecture": {"class": "partial", "link": "https://arxiv.org/abs/2312.06550", "notes": "Architecture described in preprint, but not all details documented."}, "preprint": {"class": "open", "link": "https://arxiv.org/abs/2312.06550", "notes": "Preprint describes architecture, design choices, training and fine-tuning."}, "paper": {"class": "closed", "link": null, "notes": "No peer-reviewed paper yet."}, "modelcard": {"class": "partial", "link": "https://huggingface.co/LLM360/AmberChat", "notes": "Model card doesn't specify use or limitations"}, "datasheet": {"class": "partial", "link": "https://huggingface.co/datasets/LLM360/AmberDatasets", "notes": "Concise description (better than most), but doesn't specify funders, purposes, representativeness, legal status as prescribed by datasheets industry standard"}, "package": {"class": "closed", "link": null, "notes": "No released package found"}, "api": {"class": "open", "link": "https://huggingface.co/LLM360/AmberChat", "notes": "Free Huggingface inference API."}}

field_datasheet_notes:
Concise description (better than most), but doesn't specify funders, purposes, representativeness, legal status as prescribed by datasheets industry standard


id: MPT-7b-instruct
git_filename: projects/MPT-7b-instruct.yaml
format: yaml
field_project_name: MPT-7B Instruct
field_project_link: https://huggingface.co/mosaicml/mpt-7b-instruct
field_project_llmbase: MosaicML
field_project_rlbase: dolly, anthropic
field_project_license: CC-By-SA-3.0
field_org_name: MosaicML
field_org_link: https://www.mosaicml.com
field_opencode_class: open
field_opencode_link: https://github.com/mosaicml/llm-foundry/tree/main/llmfoundry/models/mpt
field_opencode_notes: Codebase part of LLM foundry
field_llmdata_class: partial
field_llmdata_link: https://huggingface.co/datasets/c4
field_llmdata_notes: C4 is part of the dataset but a precise specification of source data is hard to find
field_llmweights_class: open
field_llmweights_link: https://huggingface.co/mosaicml/mpt-7b-instruct/tree/main
field_llmweights_notes: Weights available via HuggingFace
field_rldata_class: partial
field_rldata_link: https://huggingface.co/datasets/mosaicml/dolly_hhrlhf
field_rldata_notes: dolly-hhrlhf, combination of Databrick dolly-15k dataset and a filtered subset of Anthropic HH-RLHF
field_rlweights_class: closed
field_license_class: open
field_license_notes: CC-by-SA 3.0
field_code_class: open
field_code_link: https://github.com/mosaicml/llm-foundry/
field_code_notes: LLM Foundry codebase is well-documented and in active development
field_architecture_class: partial
field_architecture_link: https://huggingface.co/mosaicml/mpt-7b-instruct
field_architecture_notes: Architecture reasonably well-documented
field_preprint_class: closed
data:
{"project": {"name": "MPT-7B Instruct", "link": "https://huggingface.co/mosaicml/mpt-7b-instruct", "notes": null, "llmbase": "MosaicML", "rlbase": "dolly, anthropic", "license": "CC-By-SA-3.0"}, "org": {"name": "MosaicML", "link": "https://www.mosaicml.com", "notes": null}, "opencode": {"class": "open", "link": "https://github.com/mosaicml/llm-foundry/tree/main/llmfoundry/models/mpt", "notes": "Codebase part of LLM foundry"}, "llmdata": {"class": "partial", "link": "https://huggingface.co/datasets/c4", "notes": "C4 is part of the dataset but a precise specification of source data is hard to find"}, "llmweights": {"class": "open", "link": "https://huggingface.co/mosaicml/mpt-7b-instruct/tree/main", "notes": "Weights available via HuggingFace"}, "rldata": {"class": "partial", "link": "https://huggingface.co/datasets/mosaicml/dolly_hhrlhf", "notes": "dolly-hhrlhf, combination of Databrick dolly-15k dataset and a filtered subset of Anthropic HH-RLHF"}, "rlweights": {"class": "closed", "link": null, "notes": null}, "license": {"class": "open", "link": null, "notes": "CC-by-SA 3.0"}, "code": {"class": "open", "link": "https://github.com/mosaicml/llm-foundry/", "notes": "LLM Foundry codebase is well-documented and in active development"}, "architecture": {"class": "partial", "link": "https://huggingface.co/mosaicml/mpt-7b-instruct", "notes": "Architecture reasonably well-documented"}, "preprint": {"class": "closed", "link": null, "notes": null}, "paper": {"class": "closed", "link": null, "notes": null}, "modelcard": {"class": "open", "link": "https://huggingface.co/mosaicml/mpt-7b-instruct", "notes": null}, "datasheet": {"class": "closed", "link": null, "notes": null}, "package": {"class": "open", "link": null, "notes": null}, "api": {"class": "closed", "link": null, "notes": null}}


