EASONEASONF
72-hour (12 × 6-hour) autoregressive Pangu-AFNO weather forecasting code for the AI4S DCU/ROCm competition environment.
pip install easoneasonf
Use the torch, onescience, and apex versions supplied by the DCU/ROCm runtime. Model weights and ERA5 data are not included.
From a workspace containing the configured data and data/checkpoints/model_bak.pth:
easoneasonf-infer
The default configuration produces 12 autoregressive 6-hour steps, saved under result/output/006h through result/output/072h.
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