Llama Family: The Open-Source AI Model Ecosystem

What is Llama Family? The Llama Family is an open-source community dedicated to promoting the development of Artificial General Intelligence (AGI) through collaborative efforts centered around Llama models and related technologies. It aims to create a platform where developers and enthusiasts can contribute to an open-source ecosystem spanning various aspects of AI, from large-scale models to smaller ones, from text to multimodal capabilities, and from software to hardware algorithm optimizations.

Key Components of Llama Family

Models: The community focuses on various Llama models open-sourced by Meta, including Llama, Llama 2, Llama 3, Code Llama, and Atom. These models cover a range of parameter sizes and training datasets, catering to different use cases and research directions.
Compute: The community encourages collaboration and resource sharing for model training and experimentation. This includes utilizing GPU resources such as GeForce RTX series, NVIDIA H100, and A100 Tensor Core GPUs.
Community: Central to the Llama Family is its vibrant community of developers, researchers, and enthusiasts. The community fosters collaboration, knowledge sharing, and the co-creation of resources and tools.

Llama Models

Meta Llama

The Llama model open-sourced by Meta is widely used in both industry and academia. Versions include 1B, 3B, 8B, 70B, and 405B, with training data exceeding 15.0T tokens. Vision models include 11B and 90B, trained on over 6 billion image-text pairs.

Model	Training Data	Params	Tokens	Release Date
LLaMA	English CommonCrawl, C4, Github, Wikipedia, Gutenberg and Books3, ArXiv, Stack Exchange	7B (6.7B)	1.0T	2023/02/24
		13B (13.0B)	1.0T
		33B (32.5B)	1.4T
		65B (65.2B)	1.4T
Llama 2	A new mix of publicly available online data	7B	2.0T	2023/07/18
		13B	2.0T
		34B	2.0T
		70B	2.0T
Llama 3	A new mix of publicly available online data	8B	15.0T	2024/04/18
		70B	15.0T
Llama 3.1	Collected from publicly available sources, over 5% of the Llama 3 pretraining dataset consists of high-quality non-English data that covers over 30 languages	8B	15.0T	2024/07/23
		70B	15.0T
		405B	15.0T
Llama 3.2	Llama 3.2-Text: A new mix of publicly available online data	1B (1.23B)	9.0T	2024/09/25
		3B (3.21B)	9.0T
Llama 3.2-Vision	Pretrained on image and text pairs. The instruction tuning data includes publicly available vision instruction datasets, as well as over 3M synthetically generated examples	11B (10.6B)	6B (image, text) pairs
		90B (88.8B)	6B (image, text) pairs

Code Llama

Code Llama is trained on top of Llama 2 using code data and is categorized into Base Model, Python Model, and Instruct Model, with parameter sizes of 7B, 13B, 34B, and 70B. It supports code continuation, filling, and instruction-based programming.

Model	Training Data	Params	Type
Code Llama	Based on Llama 2, trained using a public code dataset of 500B tokens. To help the model retain natural language understanding skills, 8% of the sample data comes from natural language datasets related to code.	7B	Base Model: a foundational model for code generation tasks
			Python: a version specialized for Python
			Instruct: a fine-tuned version with human instructions and self-instruct code synthesis data
		13B
		34B
		70B

Atom

Atom, developed jointly by AtomEcho and Llama Family, is based on the Llama architecture and trained on 2.7T of Chinese and multilingual corpora, with parameter sizes including 1B, 7B, and 13B. Atom enhances the Chinese language capabilities of the Llama model.

Model	Training Data	Params	Tokens	Release Date
Atom	Chinese and multilingual encyclopedias, books, blogs, news, novels, financial data, legal data, medical data, code, paper, Chinese NLP competition datasets, etc.	1B	2.7T	2023/12/20
		7B	2.7T	2023/08/28
		13B	2.7T	2023/07/31

How to Contribute to Llama Family

Join the Community: Engage with other developers and enthusiasts through forums, chat groups, and events.
Contribute Code: Submit pull requests with bug fixes, new features, or model improvements.
Share Resources: Share datasets, training scripts, and pre-trained models with the community.
Provide Feedback: Offer feedback on existing models and tools to help improve their quality and usability.

Why is Llama Family important?

The Llama Family is important because it fosters collaboration and accelerates the development of open-source AI models. By providing a platform for developers and researchers to share resources and knowledge, the Llama Family helps to democratize access to AI technology and promote innovation.

Conclusion

The Llama Family is a growing community dedicated to advancing AI through open-source collaboration. Join the Llama Family today to contribute to the future of AI!