LLaMA Factory

LLaMA Factory is a web UI-driven fine-tuning framework that makes training and adapting large language models accessible through a graphical interface. It supports over 100 model architectures and provides a comprehensive training pipeline covering supervised fine-tuning, reward modeling, RLHF, DPO, and evaluation — all configurable through a browser-based dashboard. For users who want to fine-tune models without writing code or managing complex configurations, LLaMA Factory provides the most accessible and comprehensive training platform available.

Key Features

Web-based training UI. LLaMA Board, the built-in web interface, lets you configure training jobs visually. Select models, datasets, training methods, and hyperparameters through dropdowns and input fields. Monitor training progress with real-time loss curves and metrics. No command-line or YAML editing required for basic workflows.

100+ supported models. LLaMA Factory supports a vast range of model architectures: LLaMA, Mistral, Qwen, Phi, Gemma, ChatGLM, Baichuan, Yi, DeepSeek, and many more. New model architectures are added rapidly as they are released.

Complete training pipeline. Beyond basic supervised fine-tuning, LLaMA Factory supports LoRA, QLoRA, full fine-tuning, reward modeling, PPO-based RLHF, DPO (Direct Preference Optimization), KTO, and ORPO. This covers the entire alignment pipeline from initial training through preference optimization.

Built-in evaluation. Evaluate fine-tuned models on standard benchmarks directly within the framework. Compare base and fine-tuned model performance to validate training improvements before deployment.

Dataset management. LLaMA Factory includes a dataset management system with pre-configured popular datasets and support for custom datasets in multiple formats. The data preview feature lets you inspect training examples before launching jobs.

Export and deployment. Export fine-tuned models in various formats for deployment. Merge LoRA adapters into base models, convert to GGUF for llama.cpp, or push to Hugging Face Hub for sharing.

When to Use LLaMA Factory

Choose LLaMA Factory when you want the easiest path to fine-tuning with a visual interface, need to work with many different model architectures, or want a complete training pipeline including RLHF and DPO without separate tooling for each stage.

Ecosystem Role

LLaMA Factory is the most accessible entry point into model fine-tuning. Its web UI lowers the barrier compared to config-file approaches like Axolotl. For maximum single-GPU training speed, Unsloth is faster. For distributed multi-GPU training, Axolotl provides more control. LLaMA Factory’s breadth of supported models and training methods makes it the best choice for users who work across many architectures.