Unsloth could Finetune LLMs (DeepSeek, Llama 3, Mistral, Gemma, Qwen, Phi etc.) 2x faster with up to 80% less memory. Open-source, with free Colab notebooks. Now with reasoning capabilities!
Hi everyone！
Sharing Unsloth, an amazing open-source project that makes finetuning large language models (LLMs) significantly faster and more memory-efficient. If you've ever wanted to customize an LLM but were intimidated by the resource requirements, Unsloth is definately worth a try.
What's cool about it:
🚀 2x Speed, Up to 80% Less Memory: Massive performance gains without sacrificing accuracy.
🦙 Wide Model Support: Works with Llama 3 (all versions!), Mistral, Gemma 2, Qwen 2.5, Phi-4, and more.
💻 Free Colab Notebooks: Get started immediately, for free, with their Colab notebooks. No expensive hardware needed.
💡 Reasoning Capabilities Added: Reproduce DeepSeek-R1 "aha" moment.
🔓 Open Source: Fully open-source and actively developed.
Unsloth is all about making LLM finetuning accessible to everyone, not just those with huge GPU budgets.
Love the name, feel like the perfect antidote to procrastination. Congrats on the launch of Unsloth!
The ability to integrate DeepSeek-R1's reasoning is an awesome feature. Congratulations on the launch!
The combination of speed and memory efficiency is a game-changer, especially for those who are just venturing into this area and might not have access to high-end hardware.
Congrats on the launch! Best wishes and sending lots of wins :)
