llamafactory-docs

name

llamafactory-docs

description

USE THIS SKILL WHEN working with LLaMA Factory: fine-tuning LLMs (SFT/DPO/PPO/KTO/ORPO), LoRA/QLoRA training, dataset preparation (alpaca/sharegpt format), DeepSpeed/FSDP distributed training, LLaMA Board Web UI, model deployment (vLLM/SGLang), GRPO reinforcement learning, multimodal training, or using llamafactory-cli. Triggers on: LlamaFactory, llamafactory-cli, LLaMA Factory, llama-factory, LLaMA Board.

LLaMA Factory Documentation

LLaMA Factory is an efficient fine-tuning framework for 100+ LLMs supporting the full training-to-deployment pipeline.

• GitHub | Docs

CRITICAL: grep references/ for detailed docs before answering. Most docs are in Chinese.

Quick Start

pip install llamafactory

# LoRA SFT via CLI
llamafactory-cli train examples/train_lora/llama3_lora_sft.yaml

# Web UI
llamafactory-cli webui

# Chat
llamafactory-cli chat --model_name_or_path Qwen/Qwen2.5-7B-Instruct

# Deploy OpenAI API
llamafactory-cli api --model_name_or_path Qwen/Qwen2.5-7B-Instruct

Supported Training Methods

Method	Full	Freeze	LoRA	QLoRA
Pre-training	Yes	Yes	Yes	Yes
SFT	Yes	Yes	Yes	Yes
Reward Modeling	Yes	Yes	Yes	Yes
PPO/DPO/KTO/ORPO	Yes	Yes	Yes	Yes
GRPO	Yes	Yes	Yes	Yes

Key Capabilities

Feature	Description
600+ LLMs	Qwen3, Llama4, DeepSeek-R1, InternLM3, Mistral, etc.
400+ VLMs	Qwen3-VL, InternVL3.5, MiniCPM-V, GLM4.5-V, etc.
LoRA variants	LoRA, QLoRA, DoRA, LoRA+, LLaMAPro, LISA, RS-LoRA
RLHF	DPO, KTO, SimPO, ORPO, CPO, PPO
GRPO family	GRPO, DAPO, GSPO, SAPO, CISPO, RLOO, Reinforce++
Distributed	DDP, DeepSpeed ZeRO2/3, FSDP/FSDP2, Megatron
Quantization	AWQ, GPTQ, BNB, FP8, AQLM, HQQ, EETQ
Inference	vLLM, SGLang, LmDeploy acceleration
Web UI	LLaMA Board for training, inference, eval

Key Topics

Getting Started

• references/overview.md — Full feature overview (README)
• references/getting-started.md — Quick start (zh)
• references/installation.md — Installation (zh)
• references/architecture.md — Project structure, v0/v1 architecture, dev practices
• references/llamaboard-web-ui.md — Web UI guide (zh)

Data

• references/dataset-format.md — Dataset format spec (alpaca/sharegpt), dataset_info.json
• references/data-preparation/data-processing.md — Data processing pipeline (zh)
• references/examples.md — Training config examples

Training

• references/advanced/lora-and-quantization/lora.md — LoRA training (zh)
• references/advanced/lora-and-quantization/quantization.md — Quantization (zh)
• references/advanced/distributed/deepspeed.md — DeepSpeed (zh)
• references/advanced/distributed/parallel-dp-tp-ep-sp-cp.md — Parallelism strategies (zh)
• references/hyperparameters/data-argument.md — Data hyperparameters (zh)

Advanced

• references/advanced/custom-kernels/ — Custom kernels, fused operators
• references/dev-guide/core/ — Data engine, model engine internals
• references/dev-guide/plugins/ — Data plugins, model plugins

References

• references/ — 19 doc files (15 Chinese docs + 4 English extras)
• references/dataset-format.md — Comprehensive dataset format specification
• references/architecture.md — v0/v1 architecture, code structure, dev guide
• references/examples.md — Training configuration examples