Upload model - xpynr46w
Browse files- README.md +4 -5
- datamodule_config.yaml +1 -1
- full_experiment_config.yaml +8 -10
- model_config.yaml +17 -47
- model_weights.safetensors +2 -2
README.md
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@@ -17,7 +17,7 @@ Do not remove elements like the above surrounded by two curly braces and do not
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This model class uses satellite data, and numerical weather predictions to forecast the near-term (up to 8 hours ahead) PV power output at all Grid Service Points (GSPs) in Great Britain. More information can be found in the model repo [1]. The model repo also includes links to our workshop paper on this model and some experimental notes.
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This model uses NWP and Satellite data to predict
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- **Developed by:** openclimatefix
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- **Model type:** Fusion model
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<!-- Do not remove the lines below -->
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The training logs for this model commit can be found here:
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- [https://wandb.ai/openclimatefix/NL-Solar/runs/7s0axgkr](https://wandb.ai/openclimatefix/NL-Solar/runs/7s0axgkr)
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<!-- The hardware section is also just nice to have -->
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This model was trained using the following Open Climate Fix packages:
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- [1] https://github.com/openclimatefix/
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- [2] https://github.com/openclimatefix/ocf-data-sampler
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<!-- Especially do not change the two lines below -->
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The versions of these packages can be found below:
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-
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- ocf-data-sampler==1.0.
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This model class uses satellite data, and numerical weather predictions to forecast the near-term (up to 8 hours ahead) PV power output at all Grid Service Points (GSPs) in Great Britain. More information can be found in the model repo [1]. The model repo also includes links to our workshop paper on this model and some experimental notes.
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This is a summation model that uses NWP and Satellite data to predict national production of solar power in Netherlands. Predictions are done with 15 minutely resolution from 15 minutes to 36 hours ahead.
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- **Developed by:** openclimatefix
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- **Model type:** Fusion model
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<!-- Do not remove the lines below -->
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The training logs for this model commit can be found here:
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<!-- The hardware section is also just nice to have -->
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This model was trained using the following Open Climate Fix packages:
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- [1] https://github.com/openclimatefix/pvnet-summation
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- [2] https://github.com/openclimatefix/ocf-data-sampler
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<!-- Especially do not change the two lines below -->
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The versions of these packages can be found below:
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- pvnet_summation==1.2.0.post1+git.f4ac6580
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- ocf-data-sampler==1.0.1.post1+git.b7c40f80.dirty
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datamodule_config.yaml
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pvnet_model:
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model_id: openclimatefix-models/pvnet_nl
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revision:
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pvnet_model:
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model_id: openclimatefix-models/pvnet_nl
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revision: 8379a1f0efc213e6bafc583ccdf3c9ea7713ddd5
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full_experiment_config.yaml
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use_horizon_encoding: true
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use_solar_position: true
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force_non_crossing: true
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history_minutes:
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forecast_minutes: 2160
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interval_minutes: 15
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num_input_locations: 12
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threshold: 0.0
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datamodule:
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data_source_paths:
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file_path: /home/alex/NL/NL_regional_generation_kw.nc
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metadata_file_path: /home/alex/NL/NL_regional_metadata.csv
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satellite:
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v1/2019_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v1/2020_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v3/2023_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v3/2024_nonhrv.zarr
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nwp:
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ecmwf: /mnt/
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batch_size: 32
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num_workers: 8
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prefetch_factor: 2
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max_num_val_samples: null
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pvnet_model:
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model_id: openclimatefix-models/pvnet_nl
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revision:
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train_period:
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- null
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- '2023-12-31'
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every_n_epochs: 1
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verbose: false
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filename: epoch={epoch}-step={step}
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dirpath: /home/alex/NL/
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auto_insert_metric_name: false
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save_on_train_epoch_end: false
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logger:
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project: NL-Solar
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name: ${model_name}
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save_dir: /home/alex/NL/wandb
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offline:
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id: null
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log_model: false
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prefix: ''
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job_type: train
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group: ''
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tags: []
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sample_save_dir: /mnt/storage_u2_30tb_a/
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work_dir: ${hydra:runtime.cwd}
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model_name:
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seed: 2727831
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use_horizon_encoding: true
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use_solar_position: true
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force_non_crossing: true
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history_minutes: 60
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forecast_minutes: 2160
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interval_minutes: 15
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num_input_locations: 12
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threshold: 0.0
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datamodule:
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data_source_paths:
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generation: /home/alex/NL/NL_regional.zarr
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satellite:
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v1/2019_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v1/2020_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v3/2023_nonhrv.zarr
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- /mnt/storage_u2_30tb_a/ml_training_zarrs/sat/uk_sat_crops/v3/2024_nonhrv.zarr
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nwp:
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ecmwf: /mnt/storage_u2_30tb_a/nl_data_rechunked/ecmwf_nl_crop_rechunked/*_float32.zarr
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batch_size: 32
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num_workers: 8
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prefetch_factor: 2
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max_num_val_samples: null
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pvnet_model:
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model_id: openclimatefix-models/pvnet_nl
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revision: 8379a1f0efc213e6bafc583ccdf3c9ea7713ddd5
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train_period:
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- null
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- '2023-12-31'
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every_n_epochs: 1
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verbose: false
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filename: epoch={epoch}-step={step}
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dirpath: /home/alex/NL/summation_callbacks/${model_name}
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auto_insert_metric_name: false
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save_on_train_epoch_end: false
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logger:
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project: NL-Solar
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name: ${model_name}
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save_dir: /home/alex/NL/wandb
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offline: true
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id: null
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log_model: false
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prefix: ''
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job_type: train
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group: ''
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tags: []
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sample_save_dir: /mnt/storage_u2_30tb_a/NL_summation_samples_no_pv
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work_dir: ${hydra:runtime.cwd}
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model_name: v7_summation_horizon_no_pv
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seed: 2727831
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model_config.yaml
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_target_:
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output_quantiles:
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nwp_encoders_dict:
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ecmwf:
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_target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
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_partial_: true
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in_channels: 13
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out_features: 64
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fc_features: 32
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number_of_conv3d_layers: 4
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conv3d_channels: 32
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image_size_pixels: 10
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sat_encoder:
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_target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
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_partial_: true
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in_channels: 11
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out_features: 256
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number_of_conv3d_layers: 6
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conv3d_channels: 32
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image_size_pixels: 20
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add_image_embedding_channel: false
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output_network:
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_target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
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_partial_: true
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fc_hidden_features:
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n_res_blocks:
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res_block_layers: 2
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dropout_frac: 0.2
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forecast_minutes: 2160
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history_minutes: 60
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interval_minutes: 15
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_target_: pvnet_summation.models.horizon_dense_model.HorizonDenseModel
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output_quantiles:
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- 0.02
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- 0.1
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- 0.75
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- 0.9
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output_network:
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_target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
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_partial_: true
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fc_hidden_features: 32
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n_res_blocks: 1
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res_block_layers: 2
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dropout_frac: 0.2
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predict_difference_from_sum: true
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use_horizon_encoding: true
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use_solar_position: true
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force_non_crossing: true
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history_minutes: 60
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forecast_minutes: 2160
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interval_minutes: 15
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num_input_locations: 12
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input_quantiles:
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- 0.02
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- 0.1
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- 0.25
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- 0.5
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- 0.75
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- 0.9
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- 0.98
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model_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:b04709d3a3036e93bf6e9dc17f4cfacd8e8a0b94510a61dafff16a982e555b5f
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size 23684
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