Table of contents

llamafactory — LLaMA-Factory

A unified GUI + CLI for LLM training, fine-tuning, evaluation, and inference. Supports 100+ models out of the box.

Image tag

docker.io/manvarharsh/llamafactory:cuda12

What’s in this image

  • Base: nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04
  • Python 3.10 (conda)
  • PyTorch with CUDA 12
  • LLaMA-Factory (hiyouga/LLaMA-Factory)
  • bitsandbytes, accelerate, deepspeed, peft, trl
  • Gradio web UI
  • OpenSSH server

Default ports

PortService
22SSH
7860LLaMA-Factory web UI
8000API server

Use cases

  • Web-UI driven LLM fine-tuning (SFT, DPO, ORPO, KTO, PPO)
  • LoRA / QLoRA / full fine-tunes for Llama, Qwen, Gemma, Yi, Mistral
  • One-click model export to GGUF / vLLM / Ollama formats
  • Built-in eval against MMLU, IFEval, etc.

Environment variables

VariableDescription
ENABLE_SSHEnable SSH server
ENABLE_LLAMAFACTORYStart the web UI on port 7860
LLAMAFACTORY_EXTRA_ARGSExtra CLI args
SSH_PUBLIC_KEYPublic key for SSH

Persistence

Mount at /data. Datasets in /data/datasets/, checkpoints in /data/output/, base models in /data/models/.

See also