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.