skills.rest
hochoa13
hochoa13COMMUNITY
Explore all skills by this author →
GitHub

axolotl

Generate Axolotl YAML configurations for fine-tuning LLMs with LoRA.

Updated Mar 13, 2026
Search Tags:#llm#fine-tuning#yaml#lora#huggingface#dpo#axolotl
One-click install
npx skills add https://github.com/hochoa13/Asistente-Harlest --skill axolotl-hochoa13
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: axolotl
Source: https://github.com/hochoa13/Asistente-Harlest/tree/main/skills/mlops/training/axolotl
Command: npx skills add https://github.com/hochoa13/Asistente-Harlest --skill axolotl-hochoa13

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) components.

What problem does it solve?

This Skill provides expert guidance and practical examples for fine-tuning Large Language Models (LLMs) using the Axolotl framework, simplifying complex LLM customization.

Core Features & Use Cases

  • Axolotl Configuration: Understand and generate YAML configurations for various fine-tuning tasks.
  • Model Support: Leverage knowledge of over 100 models compatible with Axolotl.
  • Advanced Techniques: Implement LoRA, QLoRA, DPO, KTO, ORPO, GRPO, and multimodal fine-tuning.
  • Use Case: A user wants to fine-tune Llama 3 on a custom dataset for a specific task. They can use this Skill to generate the correct Axolotl configuration, understand the dataset formatting, and implement LoRA for efficient training.

Quick Start

Use the axolotl skill to generate a YAML configuration for fine-tuning a Llama 3 model with LoRA.

Frequently Asked Questions about axolotl

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

FAQPage Schema
How do I configure Axolotl YAML for fine-tuning LLMs like Llama 3?▼

To fine-tune LLMs like Llama 3, you generate a YAML configuration file specifying your dataset, model, and training parameters. This Skill provides expert guidance for creating Axolotl YAML configurations tailored to your specific customization tasks.

Can I use LoRA and DPO techniques for LLM fine-tuning with Axolotl?▼

Yes, you can implement advanced fine-tuning techniques including LoRA, QLoRA, DPO, KTO, ORPO, and GRPO. The Axolotl framework supports these methods to facilitate efficient Large Language Model customization on specific datasets.

What is the best way to fine-tune a Huggingface model on a custom dataset?▼

The best way to fine-tune a Huggingface model is using a framework like Axolotl to manage YAML configurations and dataset formatting. It supports over 100 models, allowing efficient customization for specific tasks using methods like LoRA.

Does Axolotl support multimodal fine-tuning for Large Language Models?▼

Yes, Axolotl supports multimodal fine-tuning alongside text-only methods. This allows you to customize Large Language Models using diverse data types beyond standard text, extending model capabilities for complex tasks.

How do I format datasets for LLM fine-tuning in Axolotl?▼

Formatting datasets for LLM fine-tuning in Axolotl requires structuring your custom data to match the target model's expected input format. This Skill provides practical examples to help you understand dataset formatting and generate correct configurations.

Related Skills

Explore More Software Engineering Skills→
Ced3-hanCed3-han

fine-tuning-with-trl

Fine-tune LLMs with TRL reinforcement learning and HuggingFace Transformers.

Community
Advanced
ScientiaCapitalScientiaCapital
1

model-deployment

Export fine-tuned models to GGUF and deploy with vLLM or Ollama.

Community
Advanced
cabeznocabezno

axolotl

Generate Axolotl YAML configurations for LoRA/QLoRA and preference-based training.

Community
Intermediate
heximaoheximao

axolotl

Automate LLM fine-tuning with Axolotl YAML configurations.

Community
Advanced