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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?

Llama 3

by Meta

Llama AI model family by Meta. This entry provides information about Llama version 3.
Text
Latest
https://huggingface.co/collections/meta-llama/meta-llama-3-66214712577ca38149ebb2b6
Meta-Llama-3-70B
Meta-Llama-3-70B-Instruct
Meta Llama 3 Community License
Meta, a major technology company.
https://ai.meta.com/
April 2024
Availability
Base Model Data
Data nowhere disclosed or documented, and described only in the vaguest terms in a release blog post
End User Model Data
No information available on instruction-tuning.
Base Model Weights
Download only after requesting access; requires signing a consent form
https://ai.meta.com/resources/models-and-libraries/llama-downloads/
End User Model Weights
Download only after requesting access; requires signing a consent form
https://ai.meta.com/resources/models-and-libraries/llama-downloads/
Training Code
Repository only offers minimal code
https://github.com/meta-llama/llama3
Documentation
Code Documentation
Code only covers minimal examples; no documentation available.
Hardware Architecture
Architecture sketched in glossy blog post.
https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
Preprint
No preprint or any other scientific documentation available.
Paper
No peer-reviewed paper available.
Modelcard
There is a model card, but it provides the absolute minimum of detail, and none whatsoever on training data.
https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md
Datasheet
Datasheet not provided.
Access
Package
Model available on Ollama.
https://ollama.com/library/llama3
API and Meta Prompts
API not available in EU.
https://llama.developer.meta.com/join_waitlist
Licenses
Even inspecting the model requires signing Meta Llama 3's bespoke 'community license', not an OSI recognised open license
https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct/tree/main
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