Download conf/config.yaml from OneScience-Group/WeatherBench: direct link, hf CLI and curl.
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https://huggingface.co/OneScience-Group/WeatherBench/resolve/main/conf/config.yaml
- Command line
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hf download hf://OneScience-Group/WeatherBench/conf/config.yaml
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curl -L -o config.yaml https://huggingface.co/OneScience-Group/WeatherBench/resolve/main/conf/config.yaml
669 Bytes
| seed: 42 | |
| data: | |
| format_version: weatherbench_v1 | |
| path: data/weatherbench.npz | |
| grid: [32, 64] | |
| samples: 24 | |
| channels: [Z500, T850] | |
| model: | |
| hidden_channels: 16 | |
| layers: 5 | |
| kernel_size: 5 | |
| train: | |
| epochs: 2 | |
| learning_rate: 0.001 | |
| paths: | |
| checkpoint: result/checkpoints/weatherbench_cnn.pt | |
| training_metrics: result/training/metrics.json | |
| predictions: result/output/predictions.npz | |
| evaluation: result/evaluation/metrics.json | |
| figure: result/evaluation/comparison.png | |
| paper_model: | |
| grid: [32, 64] | |
| input_channels: [Z500, T850] | |
| conv_layers: 5 | |
| hidden_channels: 64 | |
| kernel_size: 5 | |
| activation: ELU | |
| optimizer: Adam | |
| loss: MSE | |
| test_years: [2017, 2018] | |