🦙LLaMA-Factory
hiyouga/LlamaFactory · homepage ↗
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
⭐ Hugely popular: 74k stars, gaining about 188 a week
View on GitHub ↗repo profile
momentum
durability
bus factor = how many people it takes to cover more than half the commits (6 months). 1 is a solo project; higher means the work is spread across a team. top-author share is the single busiest author's slice of those commits.
since we covered it
why it's a big deal
- Consolidates fine-tuning across virtually all major open-source models into one consistent interface.
- Covers the full spectrum: pre-training, supervised fine-tuning, preference modeling, and RLHF variants.
- Makes cutting-edge methods like LoRA, QLoRA, DoRA, OFT, and reward modeling usable without bespoke engineering.
under the hood
- Supports over 100 LLMs and VLMs (LLaMA, Mistral, Qwen, DeepSeek, Gemma, Yi, Phi, etc.).
- CLI and WebUI powered by Gradio with OpenAI-compatible inference endpoints.
- Optimized for multiple backends (PyTorch, vLLM, DeepSpeed, FlashAttention-2, bitsandbytes).
our take from PR#18, 2025-10-01
star history
- PR#18 60k 2025-10-01
- now 74k + 15k since first covered
curve is sampled from GitHub's star history, plus our own daily readings since we covered it; the dashed stretch is before we first covered it, the solid line since. figures at coverage are the numbers we printed then (approx.), current count is live.
understory
Better known than its recent output, coasting a little on attention.
- output, commits & releases
- clout, star velocity
output = commits & releases; clout = star velocity, both 0 to 100 monthly indices; the gap where output runs above clout is the understory. The understory →
covered in
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Unified Fine-Tuning of 100+ LLMs & VLMs
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