Update README.md

README.md

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 ---
 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
+
+- GitHub: https://github.com/sumitjadhav1703/pm25-forecasting-demo
+- Live Space: https://huggingface.co/spaces/sumit1703/pm25-forecasting
+- Kaggle Competition: https://www.kaggle.com/competitions/anrf-aise-hack-phase-2-theme-2-pollution-forecasting-iitd
+
+## 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