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Unofficial org for community upload of Mistral's Open Source models.

Recent Activity
nielsr  submitted a paper 26 days ago
Scaling Test-Time Compute for Agentic Coding
nielsr  submitted a paper about 1 month ago
Geometric Context Transformer for Streaming 3D Reconstruction
nielsr  submitted a paper about 1 month ago
A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens
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danielhanchen 
posted an update 6 days ago
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5441
We’re excited to announce that Unsloth has joined the PyTorch Ecosystem! 🔥🦥

Unsloth is an open-source project that makes training & running models more accurate and faster with less compute. Our mission is to make local AI accessible to everyone. Thanks to all of you for making this possible! 💕

Blog: https://unsloth.ai/blog/pytorch
GitHub: https://github.com/unslothai/unsloth
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danielhanchen 
posted an update 10 days ago
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7580
We collaborated with NVIDIA to teach you how we made LLM training ~25% faster! 🚀

Learn how 3 optimizations help your home GPU train models faster:
1. Packed-sequence metadata caching
2. Double-buffered checkpoint reloads
3. Faster MoE routing

Guide: https://unsloth.ai/blog/nvidia-collab
GitHub: https://github.com/unslothai/unsloth
danielhanchen 
posted an update 13 days ago
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8754
We made a guide on how to run open LLMs in Claude Code, Codex and OpenClaw.

Use Gemma 4 and Qwen3.6 GGUFs for local agentic coding on 24GB RAM

Run with self-healing tool calls, code execution, web search via the Unsloth API endpoint and llama.cpp

Guide: https://unsloth.ai/docs/basics/api
danielhanchen 
posted an update 20 days ago
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10759
Unsloth is now one of the top 10 most followed organizations on Hugging Face. 🤗🦥

Thanks so much for all the support!
Our HF page:
unsloth
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nielsr 
submitted a paper to Daily Papers 26 days ago
danielhanchen 
posted an update 26 days ago
danielhanchen 
posted an update about 1 month ago
nielsr 
submitted 2 papers to Daily Papers about 1 month ago
danielhanchen 
posted an update about 1 month ago
nielsr 
submitted a paper to Daily Papers about 2 months ago
danielhanchen 
posted an update about 2 months ago
danielhanchen 
posted an update about 2 months ago
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2778
A new way to use Unsloth.

Coming soon...
MaziyarPanahi 
posted an update about 2 months ago
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2648
Training mRNA Language Models Across 25 Species for $165

We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0.40, significantly outperforming ModernBERT. We then scaled to 25 species, trained 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers. Complete results, architectural decisions, and runnable code below.

https://huggingface.co/blog/OpenMed/training-mrna-models-25-species
danielhanchen 
posted an update about 2 months ago
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937
You don’t need to set LLM parameters anymore! 🚀

llama.cpp uses only the context length + compute your local setup needs. Unsloth also auto-applies the correct model settings

Try in Unsloth Studio - now with precompiled llama.cpp binaries.

GitHub: https://github.com/unslothai/unsloth
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MaziyarPanahi 
posted an update about 2 months ago
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2298
We annotated 119K medical images with two frontier VLMs (Qwen 3.5, Kimi K2.5), cross-validated at 93% agreement, and produced 110K training records, all for under $500. Fine-tuning 3 small models (2-3B params) improved all benchmarks: best model reaches +15.0% average exact match.

Everything is open-sourced: datasets, adapters, and code.

https://huggingface.co/blog/OpenMed/synthvision
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nielsr 
submitted a paper to Daily Papers about 2 months ago
nielsr 
submitted 2 papers to Daily Papers 2 months ago
danielhanchen 
posted an update 2 months ago
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Introducing Unsloth Studio ✨
A new open-source web UI to train and run LLMs.

• Run models locally on Mac, Windows, Linux
• Train 500+ models 2x faster with 70% less VRAM
• Supports GGUF, vision, audio, embedding models
• Auto-create datasets from PDF, CSV, DOCX
• Self-healing tool calling and code execution
• Compare models side by side + export to GGUF

GitHub: https://github.com/unslothai/unsloth
Blog and Guide: https://unsloth.ai/docs/new/studio

Available now on Hugging Face, NVIDIA, Docker and Colab.