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llama-factory

Fine-tune large language models with LLaMA-Factory using no-code WebUI and QLoRA.

Updated Jan 12, 2026
Search Tags:#llm#fine-tuning#multimodal#webui#qlora#llama-factory
One-click install
npx skills add https://github.com/MesferAli/XCircle --skill llama-factory-mesferali
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llama-factory
Source: https://github.com/MesferAli/XCircle/tree/main/.claude/skills/llama-factory
Command: npx skills add https://github.com/MesferAli/XCircle --skill llama-factory-mesferali

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires llmtuner, torch, transformers, datasets, peft, accelerate, gradio, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides expert guidance and tools for fine-tuning Large Language Models (LLMs) using the LLaMA-Factory framework, enabling no-code, efficient model customization.

Core Features & Use Cases

  • No-Code Fine-Tuning: Leverage a WebUI to fine-tune over 100 models without writing code.
  • Advanced Techniques: Supports 2/3/4/5/6/8-bit QLoRA, LoRA, and multimodal fine-tuning.
  • Use Case: A researcher wants to adapt a pre-trained Llama model for a specific medical text generation task. They can use LLaMA-Factory to fine-tune the model on a custom dataset, achieving better performance for their specialized domain.

Quick Start

Use the llama-factory skill to get started with fine-tuning LLMs.

Frequently Asked Questions about llama-factory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fine-tune large language models without writing code?▼

You can fine-tune large language models without writing code by using a WebUI. This no-code approach supports customizing over 100 pre-trained models directly through graphical interfaces.

What is QLoRA fine-tuning and when should I use it for LLM customization?▼

QLoRA fine-tuning is a parameter-efficient technique that quantizes model weights to reduce memory usage. You should use it when adapting large language models on limited GPU resources.

Does LLaMA-Factory support multimodal fine-tuning?▼

Yes, multimodal fine-tuning is supported for large language models. This allows you to customize models to process and generate content across different data types.

Can I use PyTorch and Transformers to train custom medical text generation models?▼

Yes, you can adapt pre-trained models for custom medical text generation. The framework integrates PyTorch and Transformers to fine-tune models on specialized domain datasets.

What are the limitations of using a WebUI for LoRA fine-tuning?▼

Using a WebUI for LoRA fine-tuning limits advanced code-level customization and automation. For complex pipeline modifications, direct framework interaction may be required.

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