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tags:
- pytorch
- safetensors
- windformer
- esawaai
---
# WindFormer
*Developed for the ESAWAAI Project and ESAWAAI Legacy Dataset HF Bucket*
A PyTorch implementation that loads a pre-trained `WindFormerDist` architecture and prepares it in evaluation mode for inference.
## Requirements
Ensure the necessary dependencies are installed:
```bash
pip install torch safetensors
```
*Note: CUDA is utilized automatically when available; otherwise, execution defaults to the CPU.*
## File Structure
| **File** | **Description** |
| :--- | :--- |
| `main.py` | Script to load the model weights and set it to evaluation mode |
| `windformer.py` | Model architecture definition for `WindFormerDist` |
| `model.safetensors` | Pre-trained model weights |
## Execution
To run the model inference pipeline:
```bash
python main.py
```
## Model Weights & Configuration
Weights are stored using [Safetensors](https://github.com/huggingface/safetensors).
> **Important:** The instantiation parameters (e.g., `WindFormerDist(fusion=False)`) must strictly match the configuration used during training. Any discrepancy will cause `load_state_dict` to fail due to missing or unexpected keys.
## Cite
Benchaabane, A., Toft, L. D. D. S., Ristea, N.-C., Dimitriadou, K., Husson, R., Hasager, C. B., Anghel, A., Longépé, N., Mouche, A., Grouazel, A., & Datcu, M. (2026). Explainable SAR measurements for Wind Assessment with Artificial Intelligence (ESAWAAI).
## License
This dataset and its associated documentation are released under the terms of the [Creative Commons Attribution 4.0 International (CC-BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license. |