Axolotl
Axolotl is a free, open-source (Apache 2.0) framework for fine-tuning and training large language models, supporting methods like LoRA, QLoRA, and DPO through a single YAML config.
The go-to open-source toolkit for fine-tuning LLMs — free to use, GPU infrastructure is the only real cost.
Axolotl — free open-source LLM fine-tuning framework by axolotl-ai-cloud.
Axolotl is a free, Apache 2.0-licensed fine-tuning toolkit for large language models — not an 'agent framework' as the DB labels it, and not priced at $69+/month. It is purely open-source with no commercial pricing tier. The library supports a wide range of training methods (LoRA, QLoRA, DPO, GRPO, full fine-tuning) and dozens of model architectures via a single YAML config, making it one of the most capable and widely used fine-tuning frameworks in the OSS ML community.
Axolotl is the de-facto standard open-source fine-tuning harness for researchers and engineers. Its YAML-driven pipeline, comprehensive method coverage (LoRA to GRPO), Flash Attention 3/4, FSDP/DeepSpeed multi-GPU support, and active Apache 2.0 community make it hard to beat at its price point of zero.
Zero managed infrastructure — you must provision and manage your own GPUs or pay for a cloud compute provider. The learning curve to configure multi-GPU or advanced RL fine-tuning runs is steep.
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Alternatives
Unsloth or Predibase for a managed/accelerated fine-tuning service with less infrastructure overhead.
LLaMA-Factory for a simpler web-UI-driven fine-tuning experience on single GPUs.
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