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Nomi-2-Mini-GGUF
JallyAI/Nomi-2-Mini-GGUF
Nomi-2-Mini-GGUF is a image-text-to-text model from JallyAI. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
<p align="center" <img src="https://cdn-uploads.huggingface.co/production/uploads/6921fa6332f7fb129563d495/aR36SrpWzksbcGbcp84pE.png" width="128" </p
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2 GB
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.gguf2 GB · 100%
At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- apache-2.0
- Model type
- qwen3_5
- Access
- Public
- Created
- Aug 15, 2026
- Updated
- Aug 16, 2026
- SHA
- c257152a
Try a prompt
Base models
Model card
From the Hugging Face model README
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6921fa6332f7fb129563d495/aR36SrpWzksbcGbcp84pE.png" width="128">
</p>
Nomi 2.0 Mini
Introduction
Introducing Nomi 2 Mini, it was fine tuned on the same data as Nomi 2 and has a very short and efficient reasoning thanks to the RASV reasoning style. Nomi 2 Mini has only 2B parameters, half the parameters of the normal Nomi 2.
If you want to know more about Nomi 2 or RASV, checkout the Nomi 2 model card https://huggingface.com/JallyAI/Nomi-2
🌟 Key Features & Improvements
- Architecture: Qwen-3.5-2B (requires just ~1.5 GB VRAM).
- Multilingual Support: Can understand and generate text English and many other languages.
- Efficiency: Get 100+ tokens/s on consumer hardware, like an RTX 4060. You can use Nomi 2 Mini with an context window of almost 200k tokens
🧠 Training Details
- Base Model:
Qwen/Qwen3.5-2B - Fine-tuning: SFT (Supervised Fine-Tuning).
- Training Tool: Unsloth (for 4-bit optimized training).
😎 Cool License
Feel free to use or improve Nomi! Benchmark results are always welcome.
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- qwen3_5
- License
- apache-2.0
- Created
- Aug 15, 2026
- Updated
- Aug 16, 2026