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.


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