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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and 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 end user interacts with comprehensively documented and 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 end user interacts with made freely available?
Training Code
Is the source code of dataset processing, model training and tuning comprehensively 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 available in standardized format that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation?
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?

Codetulu

by Ai2

Open code model based on Llama.
Code
Full
https://huggingface.co/allenai/codetulu-2-34b
Llama-2-34B
Codetulu-2-34B
AI2 ImpACT Low-risk license
Allen Institute for AI (non-profit research institute)
https://allenai.org
November 2023
Availability
Base Model Data
Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta
End User Model Data
Dataset for end model published on HuggingFace. Proprietary dataset used in intermediate CodeLlama model.
https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture
Base Model Weights
Gated model available on HuggingFace.
https://huggingface.co/meta-llama/Llama-2-34b-hf
End User Model Weights
Model weights published on HuggingFace.
https://huggingface.co/allenai/codetulu-2-34b
Training Code
Training code made available on GitHub, open-source project.
https://github.com/allenai/open-instruct
Documentation
Code Documentation
Training code is well-documented.
https://github.com/allenai/open-instruct
Hardware Architecture
Hardware architecture described in paper.
https://arxiv.org/pdf/2311.10702
Preprint
Preprint made available on arXiv.
https://arxiv.org/pdf/2311.10702
Paper
No paper found.
Modelcard
Model card provides the requisite detail.
https://huggingface.co/allenai/codetulu-2-34b
Datasheet
End model data mix very well-documented, however CodeLlama and base model data are unavailable.
https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture
Access
Package
No package found.
API and Meta Prompts
No API found.
Licenses
AI2 ImpACT Low-risk license, not an OSI-approved license.
https://huggingface.co/allenai/codetulu-2-34b#model-description
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