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danielhanchenย 
posted an update 1 day ago
danielhanchenย 
posted an update 15 days ago
danielhanchenย 
posted an update 23 days ago
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5808
Weโ€™re excited to announce that Unsloth has joined the PyTorch Ecosystem! ๐Ÿ”ฅ๐Ÿฆฅ

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! ๐Ÿ’•

Blog: https://unsloth.ai/blog/pytorch
GitHub: https://github.com/unslothai/unsloth
  • 2 replies
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danielhanchenย 
posted an update 27 days ago
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7700
We collaborated with NVIDIA to teach you how we made LLM training ~25% faster! ๐Ÿš€

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
danielhanchenย 
posted an update about 1 month ago
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8845
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
danielhanchenย 
posted an update about 1 month ago
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10809
Unsloth is now one of the top 10 most followed organizations on Hugging Face. ๐Ÿค—๐Ÿฆฅ

Thanks so much for all the support!
Our HF page:
unsloth
  • 5 replies
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danielhanchenย 
posted an update about 1 month ago
danielhanchenย 
posted an update about 2 months ago
danielhanchenย 
posted an update about 2 months ago
danielhanchenย 
posted an update 2 months ago
danielhanchenย 
posted an update 2 months ago
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2796
A new way to use Unsloth.

Coming soon...
danielhanchenย 
posted an update 2 months ago
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945
You donโ€™t need to set LLM parameters anymore! ๐Ÿš€

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
  • 2 replies
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danielhanchenย 
posted an update 3 months ago
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3432
Introducing Unsloth Studio โœจ
A new open-source web UI to train and run LLMs.

โ€ข Run models locally on Mac, Windows, Linux
โ€ข Train 500+ models 2x faster with 70% less VRAM
โ€ข Supports GGUF, vision, audio, embedding models
โ€ข Auto-create datasets from PDF, CSV, DOCX
โ€ข Self-healing tool calling and code execution
โ€ข 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.
danielhanchenย 
posted an update 3 months ago
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3942
We collaborated with NVIDIA to teach you about Reinforcement Learning and RL environments. ๐Ÿ’š Learn:

โ€ข Why RL environments matter + how to build them
โ€ข When RL is better than SFT
โ€ข GRPO and RL best practices
โ€ข How verifiable rewards and RLVR work

Blog: https://unsloth.ai/blog/rl-environments
  • 4 replies
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danielhanchenย 
posted an update 3 months ago
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3465
100,000+ models trained with Unsloth have now been open-sourced on ๐Ÿค—Hugging Face! ๐Ÿฆฅ

Here are the most popular ones you can run local:
1. TeichAI - GLM-4.7-Flash distilled from Claude 4.5 Opus (high)
2. Zed - Qwen Coder 7B fine-tuned for stronger coding
3. DavidAU - Llama-3.3-8B distilled from Claude 4.5 Opus (high)
4. huihui - gpt-oss made โ€œabliberatedโ€

Links to models:
1. TeichAI: TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF
2. Zed: zed-industries/zeta
3. DavidAU: DavidAU/Llama3.3-8B-Instruct-Thinking-Claude-4.5-Opus-High-Reasoning
4. huihui: huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated

See all the 100K latest models fine-tuned with Unsloth here: https://huggingface.co/models?other=u
  • 2 replies
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danielhanchenย 
posted an update 4 months ago
danielhanchenย 
posted an update 4 months ago
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5249
We collaborated with Hugging Face to enable you to train MoE models 12ร— faster with 35% less VRAM via our new Triton kernels (no accuracy loss). ๐Ÿค—

Train gpt-oss locally on 12.8GB VRAM with our free notebooks: https://unsloth.ai/docs/new/faster-moe
  • 1 reply
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danielhanchenย 
posted an update 4 months ago
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3545
You can now run Kimi K2.5 locally! ๐Ÿ”ฅ

We shrank the 1T model to 240GB (-60%) via Dynamic 1-bit.
Get >40 tok/s on 242GB or 622GB VRAM/RAM for near full precision.

GGUF: unsloth/Kimi-K2.5-GGUF

Guide: https://unsloth.ai/docs/models/kimi-k2.5
  • 7 replies
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danielhanchenย 
posted an update 4 months ago
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2658
You can now fine-tune embedding models in our free Unsloth notebook! ๐Ÿค—

Fine-tuning embedding models improves retrieval & RAG by aligning vectors to your domain-specific notion of similarity, improving search, clustering, and recommendations on your data.

โญ Blog + Notebooks: https://unsloth.ai/docs/new/embedding-finetuning

Unsloth trains embedding models 1.8-3.3x faster with 20% less VRAM, 2x longer context & no accuracy loss vs. FA2 setups.

We'd like to thank Hugging Face and Unsloth contributor: electroglyph for making this possible!
  • 3 replies
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danielhanchenย 
posted an update 5 months ago