dicta-unsloth (Dicta

posted an update 4 days ago

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You can now fine-tune embedding models in our free Unsloth notebook! 🤗

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.

⭐ 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!

1 reply

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danielhanchen

posted an update 6 days ago

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Run GLM-4.7-Flash locally on your device with 24GB RAM!🔥

It's the best performing 30B model on SWE-Bench and GPQA. With 200K context, it excels at coding, agents, chat & reasoning.

GGUF: unsloth/GLM-4.7-Flash-GGUF

Guide: https://unsloth.ai/docs/models/glm-4.7-flash

danielhanchen

posted an update 11 days ago

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You can now do reinforcement learning training with 7× longer context and no accuracy loss, via our new batching algorithms.

Long reasoning chains in RL are costly, but now we enable you to train gpt-oss with GRPO & reach 380K context on a 192GB GPU.

Blog: https://unsloth.ai/docs/new/grpo-long-context

danielhanchen

posted an update 26 days ago

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Run Qwen-Image-2512, the new SOTA text-to-image model! 💜

It's the top performing open diffusion model and has more realistic + accurate images/text.

Run locally with 14GB RAM via our Dynamic GGUF: unsloth/Qwen-Image-2512-GGUF

Guide: https://unsloth.ai/docs/models/qwen-image-2512

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danielhanchen

posted an update about 1 month ago

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You can now run GLM-4.7, the new 355B parameter SOTA model on your local device (128GB RAM).✨

The model achieves SOTA performance on coding, agentic and chat benchmarks.

GGUF: unsloth/GLM-4.7-GGUF
Guide: https://docs.unsloth.ai/models/glm-4.7

3 replies

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danielhanchen

posted an update about 1 month ago

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Google releases FunctionGemma, a new 270M parameter model that runs on just 0.5 GB RAM.✨

Built for tool-calling, run locally on your phone at 50+ tokens/s, or fine-tune with Unsloth & deploy to your phone.

GGUF: unsloth/functiongemma-270m-it-GGUF
Docs + Notebook: https://docs.unsloth.ai/models/functiongemma

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danielhanchen

posted an update about 1 month ago

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NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥

Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.

GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3

1 reply

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danielhanchen

posted an update about 2 months ago

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Mistral's new SOTA coding models Devstral 2 can now be Run locally! (25GB RAM) 🐱
We fixed the chat template, so performance should be much better now!
24B: unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF
123B: unsloth/Devstral-2-123B-Instruct-2512-GGUF

🧡Step-by-step Guide: https://docs.unsloth.ai/models/devstral-2

danielhanchen

posted an update about 2 months ago

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Mistral's new Ministral 3 models can now be Run & Fine-tuned locally! (16GB RAM)
Ministral 3 have vision support and the best-in-class performance for their sizes.
14B Instruct GGUF: unsloth/Ministral-3-14B-Instruct-2512-GGUF
14B Reasoning GGUF: unsloth/Ministral-3-14B-Reasoning-2512-GGUF

🐱 Step-by-step Guide: https://docs.unsloth.ai/new/ministral-3
All GGUFs, BnB, FP8 etc. variants uploads: https://huggingface.co/collections/unsloth/ministral-3

3 replies

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danielhanchen

posted an update about 2 months ago

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Qwen3-Next can now be Run locally! (30GB RAM)
Instruct GGUF: unsloth/Qwen3-Next-80B-A3B-Instruct-GGUF

The models come in Thinking and Instruct versions and utilize a new architecture, allowing it to have ~10x faster inference than Qwen32B.
💜 Step-by-step Guide: https://docs.unsloth.ai/models/qwen3-next

Thinking GGUF: unsloth/Qwen3-Next-80B-A3B-Thinking-GGUF

danielhanchen

posted an update 3 months ago

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You can now run Kimi K2 Thinking locally with our Dynamic 1-bit GGUFs: unsloth/Kimi-K2-Thinking-GGUF

We shrank the 1T model to 245GB (-62%) & retained ~85% of accuracy on Aider Polyglot. Run on >247GB RAM for fast inference.

We also collaborated with the Moonshot AI Kimi team on a system prompt fix! 🥰

Guide + fix details: https://docs.unsloth.ai/models/kimi-k2-thinking-how-to-run-locally

danielhanchen

posted an update 5 months ago

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Run DeepSeek-V3.1 locally on 170GB RAM with Dynamic 1-bit GGUFs!🐋
GGUFs: unsloth/DeepSeek-V3.1-GGUF

The 715GB model gets reduced to 170GB (-80% size) by smartly quantizing layers.

The 1-bit GGUF passes all our code tests & we fixed the chat template for llama.cpp supported backends.

Guide: https://docs.unsloth.ai/basics/deepseek-v3.1

danielhanchen

posted an update 6 months ago

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Run OpenAI's new gpt-oss models locally with Unsloth GGUFs! 🔥🦥
20b GGUF: unsloth/gpt-oss-20b-GGUF
120b GGUF: unsloth/gpt-oss-120b-GGUF

Model will run on 14GB RAM for 20b and 66GB for 120b.

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danielhanchen

posted an update 6 months ago

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It's Qwen3 week! 💜 We uploaded Dynamic 2-bit GGUFs for:

Qwen3-Coder: unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF
Qwen3-2507: unsloth/Qwen3-235B-A22B-Instruct-2507-GGUF

So you can run them both locally!
Guides are in model cards.

1 reply

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danielhanchen

posted an update 7 months ago

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Made some 245GB (80% size reduction) 1.8bit quants for Kimi K2!

unsloth/Kimi-K2-Instruct-GGUF

danielhanchen

posted an update 7 months ago

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We fixed more issues! Use --jinja for all!
* Fixed Nanonets OCR-s unsloth/Nanonets-OCR-s-GGUF
* Fixed THUDM GLM-4 unsloth/GLM-4-32B-0414-GGUF
* DeepSeek Chimera v2 is uploading! unsloth/DeepSeek-TNG-R1T2-Chimera-GGUF

danielhanchen

posted an update 7 months ago

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Gemma 3n finetuning is now 1.5x faster and uses 50% less VRAM in Unsloth!

Click "Use this model" and click "Google Colab"!

unsloth/gemma-3n-E4B-it

unsloth/gemma-3n-E2B-it

https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_(4B)-Conversational.ipynb

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danielhanchen

posted an update 7 months ago

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We updated lots of our GGUFs and uploaded many new ones!
* unsloth/dots.llm1.inst-GGUF
* unsloth/Jan-nano-GGUF
* unsloth/Nanonets-OCR-s-GGUF
* Updated and fixed Q8_0 upload for unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF
* Added Q2_K_XL for unsloth/DeepSeek-R1-0528-GGUF
* Updated and fixed Vision support for unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF

danielhanchen

posted an update 8 months ago

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Mistral releases Magistral, their new reasoning models! 🔥
GGUFs to run: unsloth/Magistral-Small-2506-GGUF

Magistral-Small-2506 excels at mathematics and coding.

You can run the 24B model locally with just 32GB RAM by using our Dynamic GGUFs.

danielhanchen

posted an update 8 months ago

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New DeepSeek-R1-0528 1.65-bit Dynamic GGUF!

Run the model locally even easier! Will fit on a 192GB Macbook and run at 7 tokens/s.

DeepSeek-R1-0528 GGUFs: unsloth/DeepSeek-R1-0528-GGUF
Qwen3-8B DeepSeek-R1-0528 GGUFs: unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF

And read our Guide: https://docs.unsloth.ai/basics/deepseek-r1-0528

Dicta - Unsloth

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