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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and freely made available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Data
Are datasources for training the model that the enduser interacts with comprehensively documented and freely made available?
Base Model Weights
Are the weights of the base models made freely available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Weights
Are the weights of the model that the enduser interacts with made freely available?
Training Code
Is the source code of datasource processing, model training and tuining comprehensively and freely made available?
Code Documentation
Is the source code of datasource processing, model training and tuning comprehensively documented?
Hardware Architecture
Is the hardware architecture used for datasource processing and model training comprehensively documented?
Preprint
Are archived preprint(s) are available that detail all major parts of the system including datasource processing, model training and tuning steps?
Paper
Are peer-reviewed scientific publications available that detail all major parts of the system including datasource processing, model training and tuning steps?
Modelcard
Is a model card in standardized format available that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation are available?
Datasheet
Is a datasheet as defined in "Datasheets for Datasets" (Gebru et al. 2021) available?
Package
Is a packaged release of the model available on a software repository (e.g. a Python Package Index, Homebrew)?
API and Meta Prompts
Is an API available that provides unrestricted access to the model (other than security and CDN restrictions)? If applicable, this entry also collects information on the use and availability of meta prompts.
Licenses
Is the project fully covered by Open Source Initiative (OSI)-approved licenses, including all data sources and training pipeline code?

Tülu

by Ai2

Tülu, a Llama-based model from AllenAI with a relatively open post-training recipe.
Text
Full
https://huggingface.co/allenai/Llama-3.1-Tulu-3-405B
Llama-3.1-405B
Llama-3.1-Tulu-3-405B
Llama 3.1 Community License Agreement
Allen Institute for AI (non-profit research institute)
https://allenai.org
June 2023
Availability
Training Code
Important effort to make available fine-tuning procedure and source code.
https://github.com/allenai/open-instruct
Base Model Data
Based on Llama3.1 so nothing known about pre-training data of base mode.
End User Model Data
Data sources outlined in paper.
https://arxiv.org/pdf/2411.15124
Base Model Weights
Gated model available through HuggingFace.
https://huggingface.co/meta-llama/Llama-3.1-405B
End User Model Weights
Model weights available through HuggingFace.
https://huggingface.co/allenai/Llama-3.1-Tulu-3-405B
Documentation
Code Documentation
OpenInstruct code well-documented.
https://github.com/allenai/open-instruct
Hardware Architecture
Fine-tuning hardware architecture well-documented, but base model is irrevocably closed.
https://huggingface.co/allenai/Llama-3.1-Tulu-3-405B
Preprint
Preprint available through arXiv.
https://arxiv.org/pdf/2411.15124
Paper
No peer-reviewed work found.
Modelcard
Model card provides the requisite detail.
https://huggingface.co/allenai/Llama-3.1-Tulu-3-405B
Datasheet
Some datasheets available (for instruction tuning), but base model entirely undocumented.
https://arxiv.org/pdf/2411.15124
Access
Package
Model available on Ollama.
https://ollama.com/library/tulu3
API and Meta Prompts
Available via various APIs.
https://playground.allenai.org/
Licenses
Llama 3.1 Community License Agreement, not an OSI-approved license.
https://huggingface.co/allenai/Llama-3.1-Tulu-3-405B#model-description
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