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Unsloth - AI Model Libraries & Training Tool

Overview

Unsloth is an open-source tool that helps developers finetune various large language models more efficiently. It provides free notebooks, dynamic quantization to reduce memory usage, and faster training to simplify deployment to GGUF, Ollama, vLLM, and Hugging Face.

Key Features

  • Finetune Llama 4, DeepSeek-R1, Gemma 3, and other large language models
  • Free notebooks for examples, experiments, and reproducible workflows
  • Dynamic quantization to reduce memory usage during training
  • Faster training performance compared with standard workflows
  • Export and deploy optimized models to GGUF, Ollama, vLLM, and Hugging Face

Ideal Use Cases

  • Finetuning research-scale models locally
  • Reducing GPU memory footprint for model training
  • Preparing optimized models for GGUF or Hugging Face deployment
  • Rapid prototyping and experimentation using provided notebooks

Getting Started

  • Clone the Unsloth repository from GitHub
  • Open the provided free notebooks to review examples
  • Prepare and format your training dataset
  • Configure the target model and dynamic quantization settings
  • Run the finetuning workflow using the notebooks or scripts
  • Export the optimized model for GGUF, Ollama, vLLM, or Hugging Face

Pricing

No pricing information provided; Unsloth is distributed as an open-source repository.

Key Information

  • Category: Model Libraries & Training
  • Type: AI Model Libraries & Training Tool
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