LlamaFactory open source analysis

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Project overview

⭐ 64963 · Python · Last activity on GitHub: 2026-01-05

GitHub: https://github.com/hiyouga/LlamaFactory

Why it matters for engineering teams

LlamaFactory addresses the practical challenge of efficiently fine-tuning over 100 large and vision language models, enabling engineering teams to adapt state-of-the-art AI models to specific tasks without excessive resource demands. It is particularly suited for machine learning and AI engineering teams focused on deploying customised models in production environments. The project demonstrates a high level of maturity, backed by recent academic validation and a growing user base, making it a reliable choice for production use. However, it may not be the best fit for teams seeking out-of-the-box solutions or those with limited expertise in model fine-tuning, as it requires a solid understanding of large language models and tuning techniques. The trade-off lies in balancing flexibility and control against ease of use and setup complexity.

When to use this project

This open source tool for engineering teams is a strong choice when fine-tuning large language or vision models efficiently is a priority, especially in scenarios demanding customisation and resource optimisation. Teams should consider alternatives if they need simpler, pre-trained models or fully managed services with minimal configuration.

Team fit and typical use cases

Machine learning engineers and AI specialists benefit most from LlamaFactory, using it to fine-tune models tailored to their specific data and use cases. It commonly appears in products requiring advanced natural language processing or vision capabilities, such as recommendation systems, chatbots, and custom AI assistants. As a production ready solution, it offers a self hosted option for teams wanting full control over their model training workflows.

Best suited for

Topics and ecosystem

agent ai deepseek fine-tuning gemma gpt instruction-tuning large-language-models llama llama3 llm lora moe nlp peft qlora quantization qwen rlhf transformers

Activity and freshness

Latest commit on GitHub: 2026-01-05. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.