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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 3.1

by Meta

Find this model in our guide:
Llama and BloomZ: shades of openness
12 October 2024
Llama AI model family by Meta. This entry provides information about Llama version 3.1.
Text
Latest
https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct
Llama-3.1-405B
Llama-3.1-405B-Instruct
Meta Llama 3 Community License
Meta, a major technology company.
https://ai.meta.com/
July 2024
Availability
Base Model Data
Data nowhere disclosed or documented, and described in the llama 3.1 paper as "obtained from the web"
End User Model Data
No information available on instruction-tuning.
Base Model Weights
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license
https://huggingface.co/meta-llama/Meta-Llama-3.1-8B
End User Model Weights
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license
Training Code
Repository only offers code for inference pipeline
https://github.com/meta-llama/llama3
Documentation
Code Documentation
Code provide only model architecture and an inferencing pipeline examples; some files are documented.
Hardware Architecture
Architecture described in paper, energy consumption and environmental impact disclosed in model card, but not in paper; training process not fully documented
https://ai.meta.com/research/publications/the-llama-3-herd-of-models/
Preprint
Technical report mentions some details about architecture but none about data used for pre and post-training.
https://arxiv.org/abs/2407.21783https://ai.meta.com/blog/meta-llama-3-1/
Paper
No peer-reviewed paper available.
Modelcard
There is a model card, but it does not disclose the training process
https://huggingface.co/meta-llama/Meta-Llama-3.1-405B
Datasheet
No datasheet found, and nothing is known about the data used for training or fine-tuning.
Access
Package
Package is provided in Pypi
https://pypi.org/project/llama-models/
API and Meta Prompts
API not available in EU.
https://llama.developer.meta.com/join_waitlist
Licenses
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license
https://huggingface.co/meta-llama/Meta-Llama-3.1-8B
Last updated 10 June 2025
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