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"model_name": "MetNet-3 Compact",
"model_type": "metnet3-compact",
"architectures": [
"MetNet3"
],
"framework": "PyTorch",
"domain": "atmosphere",
"task": "regional-probabilistic-weather-forecasting",
"implementation": {
"entry_point": "model/metnet3.py",
"scope": "compact smoke implementation; channel counts and output bins are reduced from the paper model"
},
"architecture": {
"family": "multi-source convolutional encoder-decoder with MaxViT",
"hidden_size": 32,
"maxvit_blocks": 1,
"condition_size": 16,
"conditioning_inputs": [
"current_time",
"lead_time"
]
},
"input_schema": {
"mrms_high_channels": 4,
"mrms_low_channels": 3,
"omo_channels": 2,
"hrrr_proxy_channels": 8,
"goes_proxy_channels": 4,
"high_resolution_frames": 3,
"omo_frames": 3,
"default_fake_grid_shape": [
8,
8
]
},
"output_schema": {
"precipitation_bins": 16,
"surface_variables": 6,
"surface_variable_bins": 8,
"hrrr_regression_channels": 8
},
"configuration_sources": [
"model/metnet3.py",
"model/metnet3_schema.py",
"README.md"
]
}
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