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README.md

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----
-license: mit
----
+---
+language: en
+license: mit
+library_name: pytorch
+---
+
+
+# Cloudcasting
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+This model is trained to predict future frames of satellite data from past frames. It takes 3 hours
+of recent satellkite imagery at 15 minute intervals and predicts 3 hours into the future also at
+15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels.
+
+
+See [1] for the repo used to train the model.
+
+- **Developed by:** Open Climate Fix and the Alan Turing Institute
+- **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. -->
+This was trained on EUMETSAT satellite imagery derived from the data stored in [this google public 
+dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss?hl=en-GB&inv=1&invt=AbniZA&project=solar-pv-nowcasting&pli=1). 
+
+The data was processed using the protocol in [2]
+
+
+
+## Results
+
+The training logs for the current model can be found here:
+- https://wandb.ai/openclimatefix/sat_pred/runs/ob9v9128
+
+
+### Software
+
+- [1] https://github.com/openclimatefix/sat_pred
+- [2] https://github.com/alan-turing-institute/cloudcasting

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cc35b136a9b0383cc989af09f3b370693a5a147835132282d9086af9e1579e8e
+size 55940132

model_config.yaml

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+_target_: sat_pred.models.simvp_model.SimVP
+forecast_len: 12
+history_len: 12
+num_channels: 11