Introducing Unsloth Studio ✨
Today, we’re excited to launch Unsloth Studio (Beta): an open-source, no-code web UI for training, running and exporting open models in one unified local interface.
Run GGUF and safetensor models locally on Mac, Windows, Linux.
Train 500+ models 2x faster with 70% less VRAM (no accuracy loss)
Run and train text, vision, TTS audio, embedding models
MacOS and CPU work for Chat GGUF inference. MLX training coming soon.
Export your model to GGUF, 16-bit safetensor etc.
Auto inference parameter tuning and edit chat templates.
Unsloth Studio allows Self-healing tool calling / web search + code execution. LLMs can run code and programs in a sandbox so it can calculate, analyze data, test code, generate files, or verify an answer with actual computation. This makes answers from models more reliable and accurate.
No dataset needed. Transform PDFs, CSV, DOCX, TXT or any file into a structured synthetic datasets via Unsloth Data Recipes. Build and edit your datasets visually via a graph-node workflow and use them for fine-tuning.
Unsloth Studio provides the complete workflow, from data preparation and training to observability, inference, export, and deployment. You can now use Unsloth Studio locally via GitHub:
Thank you so much for the support as always. Thank you to NVIDIA and Hugging Face for being great partners. We hope to release multiGPU and Apple Silicon MLX training very soon!