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README.md

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 ---
+language: en
 license: mit
+library_name: pytorch
 ---
+
+
+
+
+
+
+# PVNet2
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+This model class uses satellite data, numericl weather predictions, and recent Grid Service Point( GSP) PV power output to forecast the near-term (~8 hours) PV power output at all GSPs. More information can be found in the model repo [1] and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
+
+- **Developed by:** openclimatefix
+- **Model type:** Fusion model
+- **Language(s) (NLP):** en
+- **License:** mit
+
+
+# Training Details
+
+## Data
+
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+The model is trained on data from 2017-2020 and validated on data from 2021. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) for more details.
+
+
+### Preprocessing
+
+Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [2].
+
+
+## Results
+
+The training logs for the current model can be found [here on wandb](https://wandb.ai/openclimatefix/pvnet2.1/runs/None).
+
+The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
+
+Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
+
+
+### Hardware
+
+Trained on a single NVIDIA Tesla T4
+
+### Software
+
+- [1] https://github.com/openclimatefix/PVNet
+- [2] https://github.com/openclimatefix/ocf_datapipes

config.json

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+{
+    "_target_": "pvnet_summation.models.model.Model",
+    "output_quantiles": [
+        0.1,
+        0.5,
+        0.9
+    ],
+    "model_name": "openclimatefix/pvnet_v2",
+    "model_version": "96ac8c67fa8663844ddcfa82aece51ef94f34453",
+    "output_network": {
+        "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
+        "_partial_": true
+    },
+    "output_network_kwargs": {
+        "fc_hidden_features": 128,
+        "n_res_blocks": 2,
+        "res_block_layers": 4,
+        "dropout_frac": 0.0
+    },
+    "predict_difference_from_sum": true,
+    "optimizer": {
+        "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",
+        "lr": 0.0001,
+        "weight_decay": 0.5,
+        "amsgrad": true,
+        "patience": 5,
+        "factor": 0.1,
+        "threshold": 0.002
+    },
+    "scale_pvnet_outputs": true
+}

pytorch_model.bin

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