[NEW MODEL] SupraWeather-Nano-Preview Just released!

SupraWeather Nano is live! ⛈️

We just released SupraWeather-Nano (preview), a small FT-Transformer model purpose-built to classify weather phenomena from raw tabular meteorological features.

https://huggingface.co/SupraLabs/SupraWeather-Nano-Demo

https://huggingface.co/SupraLabs

Most weather classification setups either bolt a generic model onto tabular data or skip structure entirely. SupraWeather Nano uses a dedicated Feature Tokenizer + Transformer Encoder (FT-Transformer), each input feature gets its own learned token, a CLS token aggregates them, and a small transformer stack does the rest. No system prompt, no text input. Just send the numbers and get a class back.

Inputs: temperature, humidity, pressure, pressure trend, wind speed, wind direction, altitude, month, air mass.

Examples:

Quick start:

*FULL CODE ON REPO* 

Live demo (Space): https://huggingface.co/spaces/SupraLabs/SupraWeather-Nano-Preview

This is a preview release trained entirely on a synthetic dataset (rule-based generator, 120k samples). It is not intended for real-world forecasting, it's an architecture and pipeline experiment. 5/6 internal stress tests pass; the one failure (windstorm vs. cold front) is documented in the model card.

Feedback welcome!