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Nomi-2-Mini – AI Model by JallyAI | AlphaNeural AI
You can deploy this model and start earning money today!
JallyAI
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Nomi-2-Mini
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transformers
safetensors
qwen3_5
image-text-to-text
efficient
qwen
qwen3.5
nomi
lazyloopstudio
unsloth
nomi2
conversational
Qwen/Qwen3.5-2B
finetune
apache-2.0
endpoints_compatible
us
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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.
