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axolotl

Guide fine-tuning of large language models with Axolotl configurations and advanced techniques.

6|3|Updated Jan 29, 2026
Search Tags:#llm#machine learning#model training#fine-tuning#deep learning#axolotl
One-click install
npx skills add https://github.com/jonnabio/ace-framework --skill axolotl-jonnabio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: axolotl
Source: https://github.com/jonnabio/ace-framework/tree/main/.ace/packs/ai-research/axolotl
Command: npx skills add https://github.com/jonnabio/ace-framework --skill axolotl-jonnabio

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides expert guidance for fine-tuning large language models (LLMs) using Axolotl, offering configurations, 100+ models, and advanced techniques like LoRA, QLoRA, DPO, KTO, ORPO, GRPO, and multimodal support.

Core Features & Use Cases

  • Model Fine-Tuning: Offers expert guidance for configuring and fine-tuning LLMs with Axolotl.
  • Advanced Techniques: Covers LoRA, QLoRA, DPO, KTO, ORPO, GRPO for enhanced model performance.
  • Multimodal Support: Supports various multimodal data types for enhanced LLM capabilities.
  • Use Case: Suppose you have a specific LLM that requires fine-tuning with LoRA for improved performance. This Skill can guide you through the process, from setting up the environment to fine-tuning the model and evaluating the results.

Quick Start

Use the axolotl skill to fine-tune the 'gpt2' model with LoRA for a specific task.

Frequently Asked Questions about axolotl

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

FAQPage Schema
How do I fine-tune a large language model with LoRA using Axolotl?▼

Axolotl supports advanced preference alignment techniques including DPO, KTO, ORPO, and GRPO. These methods enhance model performance by optimizing human preferences during the fine-tuning process, and this Skill offers expert guidance for configuring them in your YAML setup.

Can I use Axolotl for multimodal model fine-tuning?▼

Fine-tuning LLMs with Axolotl requires PyTorch, Transformers, Datasets, PEFT, Accelerate, and DeepSpeed dependencies. This Skill guides you through the environment setup and configuration required to successfully launch model training with these frameworks.

What is the best way to configure YAML files for LLM training in Axolotl?▼

The best way to configure YAML files for LLM training in Axolotl is to define your base model, dataset paths, and training technique parameters like LoRA or DPO. This Skill provides expert guidance for structuring these configurations to fine-tune over 100 supported models.

Does Axolotl work with DeepSpeed and PEFT for model fine-tuning?▼

Yes, Axolotl works with DeepSpeed and PEFT to optimize large language model fine-tuning. This Skill helps you leverage these dependencies alongside Accelerate and Transformers to distribute training workloads and apply parameter-efficient techniques like QLoRA.

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