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llama-factory

Guide fine-tuning of large language models with LLaMA-Factory WebUI.

Updated Apr 30, 2026
Search Tags:#fine-tuning#multimodal#webui#huggingface#qlora#llama-factory#language models
One-click install
npx skills add https://github.com/Ced3-han/Harness-Settings --skill llama-factory-ced3-han
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llama-factory
Source: https://github.com/Ced3-han/Harness-Settings/tree/main/skills/llama-factory
Command: npx skills add https://github.com/Ced3-han/Harness-Settings --skill llama-factory-ced3-han

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 for fine-tuning LLMs with LLaMA-Factory, offering a WebUI for no-code access to over 100 models and features like QLoRA and multimodal support.

Core Features & Use Cases

  • Fine-Tuning Guidance: Offers comprehensive assistance with llama-factory development, including training, debugging, and best practices.
  • WebUI: Allows for no-code fine-tuning of LLMs, accessible through a web interface.
  • Models: Provides access to over 100 pre-trained models, including QLoRA and multimodal options.
  • Use Case: Imagine you want to fine-tune a language model for a specific task, like code generation or question answering. This Skill can guide you through the process, from selecting the appropriate model to fine-tuning it with your specific data.

Quick Start

Use the llama-factory skill to fine-tune the 'gpt-3' model with your custom data.

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 LLMs without writing code using a WebUI?▼

You can fine-tune LLMs without code by using LLaMA-Factory's WebUI, which provides a Gradio-based graphical interface for no-code training and configuration of over 100 models.

Can I use QLoRA for fine-tuning language models with this setup?▼

Yes, you can use QLoRA for fine-tuning language models. LLaMA-Factory supports QLoRA, allowing efficient parameter-efficient fine-tuning alongside other methods for tasks like code generation and text summarization.

What dependencies do I need to install for LLM fine-tuning with LLaMA-Factory?▼

To fine-tune LLMs with LLaMA-Factory, you need to install dependencies including llmtuner, torch, transformers, datasets, peft, accelerate, and gradio to ensure the training environment functions correctly.

Does LLaMA-Factory support multimodal models for fine-tuning?▼

Yes, LLaMA-Factory supports multimodal models for fine-tuning. It provides access to over 100 pre-trained models, including multimodal options, enabling training across diverse data types and tasks.

What is the best way to start fine-tuning a huggingface model for question answering?▼

The best way to start fine-tuning a huggingface model for question answering is using LLaMA-Factory, which guides you from selecting an appropriate pre-trained model to fine-tuning it with your specific custom data.

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