{
  "model_type": "fela_grid_renewable",
  "description": "Dual path FNO probabilistic power forecaster for solar and wind, trained on GEFCom2014. Outputs 99 quantiles per hour from weather covariates.",
  "architecture": "fno_dual_path",
  "framework": "pytorch",
  "architectures": [
    "FelaGridModel"
  ],
  "auto_map": {
    "AutoConfig": "configuration_grid.FelaGridConfig",
    "AutoModel": "modeling_grid.FelaGridModel"
  },
  "default_track": "solar",
  "tracks": {
    "solar": {
      "params": 136780,
      "input_steps": 6,
      "input_features": 20,
      "input_shape": [1, 6, 20],
      "weights_safetensors": "solar.safetensors",
      "dims": {"Fin": 20, "L": 6, "D": 64, "modes": 3, "nblk": 4, "nq": 99, "arch": "dual"}
    },
    "wind": {
      "params": 311554,
      "input_steps": 12,
      "input_features": 15,
      "input_shape": [1, 12, 15],
      "weights_safetensors": "wind.safetensors",
      "dims": {"Fin": 15, "L": 12, "D": 96, "modes": 6, "nblk": 3, "nq": 99, "arch": "dual"}
    }
  },
  "num_quantiles": 99,
  "quantile_levels_percent": "1..99",
  "output_shape": "[batch, 99]",
  "output_units": "power as fraction of site rated capacity (0 to 1), 99 monotone quantiles for the center forecast hour",
  "preprocessing": "standardize the NWP window per feature; RevIN runs inside the model. See modeling.preprocess_nwp",
  "license": "lowdown-labs-lovely-license-1.0"
}