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sumit1703
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pm25-forecasting-data

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air-quality
pm25
pollution-forecasting
gradio
numpy
kaggle
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metadata 
license: mit
tags:
  - air-quality
  - pm25
  - pollution-forecasting
  - gradio
  - numpy
  - kaggle
  - aisehack
pretty_name: PM2.5 Forecasting Demo Data
size_categories:
  - n<1K

PM2.5 Forecasting Demo Data

This dataset stores the lightweight artifacts used by the Hugging Face Space demo:

https://huggingface.co/spaces/sumit1703/pm25-forecasting

The files are precomputed outputs from the ANRF AISEHack Phase 2 Theme 2 Pollution Forecasting project. The Space uses these artifacts only for visualization. It does not run live model inference, training, or torch at runtime.

Files

File Description
demo_preds.npy Precomputed PM2.5 forecast predictions for demo windows. Shape: (22, 140, 124, 16)
demo_inputs.npy Input PM2.5 history windows used for comparison. Shape: (22, 10, 140, 124)
lat_lon.npy Latitude/longitude grid used for map axes.
demo_stats.json Feature normalization/statistics metadata from the preprocessing pipeline.
sample_indices.npy Original sample/window indices used by the demo. Shape: (22,)

Intended Use

This dataset is intended for the companion Gradio demo only. It allows the app to load saved prediction artifacts from the Hugging Face Hub instead of storing .npy files inside the GitHub repository.

Source Project

Notes and Limitations

  • These files are for demo visualization, not full model training.
  • The dataset contains a small subset of demo windows, not the complete competition dataset.
  • The predictions are precomputed and static.
  • The Space downloads these files at startup using huggingface_hub.

License

MIT