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Axolotl project preview

Axolotl

Post-train and fine-tune various AI models with ease on diverse hardware setups.

LicenseApache-2.0
GitHub stars8.5k
Last commit1 weeks ago
Tags6 topics
Python AiQlora TrainingLlm FinetuningYaml ConfigsArtificial IntelligenceDpo Alignment
Overview

Why consider Axolotl?

Axolotl is a popular open-source fine-tuning and post-training framework for LLMs written in Python. It supports LoRA, QLoRA, full parameter fine-tuning, DPO, and PPO alignments across Llama 3, Mistral, and Gemma models using simple YAML configuration files.

Guided learning

Learn Axolotl by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 2 sections
In this guide2 sections

Overview of Axolotl

Axolotl streamlines fine-tuning pipelines with support for Flash Attention 2, DeepSpeed ZeRO, and FSDP.

Quickstart

bash
1pip install -e .
2accelerate launch -m axolotl.cli.train config.yaml

Axolotl is licensed under the Apache License Version 2.0.

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Axolotl FAQs

Axolotl is listed as a Developer Tools tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository and official website for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

Axolotl is listed under the Apache-2.0 license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

Axolotl is listed as an alternative to Predibase. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.