Unsloth AI software

Unsloth AI (often referred to as 'Unsloth' or 'Unsloth Souped Up') is an open-source framework specifically designed to accelerate and optimize the fine-tuning of Large Language Models (LLMs) such as Llama 3, Mistral, and Qwen. Founded by brothers Daniel and Michael Han, the brand emerged to solve the computational inefficiencies commonly found in standard deep learning libraries. By utilizing custom hand-written kernels and specialized memory management techniques, Unsloth allows developers to train models significantly faster and with much lower memory overhead compared to traditional methods.

The project is digitally developed and maintained primarily in the United States, though it benefits from a wide contributor base in the global open-source community. It has become a staple tool for developers looking to run 'QLoRA' or 'LoRA' fine-tuning on consumer-grade hardware, making advanced AI development far more accessible.

Owned by Unsloth AI Inc., the brand maintains its headquarters in San Francisco, California. Since its inception, the company has grown from a popular GitHub repository into a venture-backed startup, securing funding from prominent tech investors to further enhance the performance of generative AI workflows.