{
  "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"
  ]
}