Unsloth

About

This MCP server integrates Unsloth, a library designed to drastically improve the efficiency of fine-tuning large language models. Unsloth achieves significant speed improvements and reduces VRAM usage through custom CUDA kernels, optimized backpropagation, and dynamic 4-bit quantization. With support for popular models like Llama, Mistral, and Gemma, the server offers tools for loading, fine-tuning, generating text, and exporting models in various formats, making it easier to optimize and deploy LLMs on consumer GPUs.

Key Features

• Supports extended context lengths for improved performance
• Implements 4-bit quantization for efficient training
• Enables exporting models to various formats (GGUF, Hugging Face, etc.)
• Provides a simple API for model loading, fine-tuning, and inference
• 1 GitHub stars
• Optimizes fine-tuning for Llama, Mistral, Phi, and Gemma models

Use Cases

• Deploying fine-tuned models in various formats for inference
• Fine-tuning large language models with limited VRAM
• Accelerating the training process for LLMs