Unsloth
Fine-tune LLMs up to 30x faster with 90% less memory usage
Unsloth is an open-source fine-tuning framework that dramatically accelerates LLM training while reducing memory usage. It supports popular models including Llama, Mistral, Phi, Gemma, and Qwen, with full compatibility with Hugging Face's transformers and TRL libraries. Unsloth achieves its speed gains through custom Triton kernels and intelligent memory optimization, requiring no changes to existing training code. Free and Pro tiers are available, with enterprise support for multi-node deployments.
Pricing: Free / monthly subscriptions
Unsloth Alternatives
Explore 19 products in the Fine-tuning category. View all Unsloth alternatives.
LLaMA-Factory
Open-source fine-tuning framework for 100+ LLMs with a web UI
Axolotl
Open-source toolkit for fine-tuning LLMs with a single YAML config across the full training pipeline
Ludwig
Declarative deep learning framework for building and fine-tuning models with YAML configuration
Hugging Face
The open-source AI platform with 500K+ models, inference endpoints, and fine-tuning tools
TRL
Hugging Face library for training language models with RLHF, SFT, and DPO
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