Axolotl

Open-source framework for fine-tuning and evaluating large language models.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Axolotl?

Axolotl simplifies the process of experimenting with different training configurations, supporting features like LoRA, QLoRA, DeepSpeed, PEFT, and multi-GPU setups. It makes it easy to reproduce and share results in LLM development.

Key differentiator

Axolotl stands out by offering a comprehensive open-source framework that simplifies the process of experimenting with different fine-tuning strategies and supports efficient reproducibility.

Capability profile

Strength Radar

Supports LoRA an…Integration with…Multi-GPU setup …PEFT (Parameter-…Easy reproducibi…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Supports LoRA and QLoRA for efficient fine-tuning

Integration with DeepSpeed for large-scale training

Multi-GPU setup support for distributed training

PEFT (Parameter-Efficient Fine-Tuning) capabilities

Easy reproducibility of results

Fit analysis

Who is it for?

✓ Best for

Research teams needing to experiment with various fine-tuning techniques on large language models

Developers looking for an open-source solution to reproduce and share their model training results

Academic researchers who require a flexible framework for LLM experimentation

✕ Not a fit for

Teams requiring real-time inference capabilities, as Axolotl focuses on training and fine-tuning

Projects with strict budget constraints, given the hardware requirements for large-scale training

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Next step

Get Started with Axolotl

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →