Unsloth
A library for fast and memory-efficient LLM fine-tuning. Unsloth optimizes the training loop with custom CUDA kernels, enabling 2-5x faster fine-tuning with 70% less memory usage. It integrates with Hugging Face Transformers and supports popular models like Llama, Mistral, and Gemma.
Implements
Concepts this tool claims to implement:
- Fine-Tuning primary
Optimized LoRA and QLoRA training. Custom triton kernels for attention and MLP layers. Gradient checkpointing with reduced memory overhead. 2-5x speedup over standard Hugging Face training.
- Quantization secondary
4-bit quantization for training (QLoRA). GGUF export for inference. Memory-efficient training on consumer GPUs.
Integration Surfaces
Details
- Vendor
- Unsloth AI
- License
- Apache-2.0
- Runs On
- local, cloud
- Used By
- human, system
Links
Notes
Unsloth makes fine-tuning accessible on limited hardware. Popular for Google Colab users who want to fine-tune LLMs on free tier GPUs. The speed improvements are significant and well-documented. Works as a drop-in optimization for existing Hugging Face training code.