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openclimatefix-models/pvnet_v2_summation
pvnet_v2_summation is a machine learning model from openclimatefix-models. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
Do not remove elements like the above surrounded by two curly braces and do not add any more of them. These entries are required by the PVNet library and are automaticall infilled when the model is uploaded to hugging…
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.safetensors1.6 MB · 99%
From the Hugging Face model README
This model class uses satellite data, and numerical weather predictions to forecast the near-term (~8 hours) PV power output at all GSPs. More information can be found in the model repo [1].
The model is trained on data from 2019-2021 and validated on data from 2022. It uses NWP data from ECMWF IFS model, and the UK Met Office UKV model. It uses also uses inputs from OCF's cloudcasting model
<!-- The preprocessing section is not strictly nessessary but perhaps nice to have -->Data is prepared with the ocf_data_sampler/torch_datasets/datasets/pvnet_uk Dataset [2].
The training logs for the current model can be found here:
<!-- The hardware section is also just nice to have --> <!-- ### Hardware Trained on a single NVIDIA Tesla T4 --> <!-- Do not remove the section below -->This model was trained using the following Open Climate Fix packages:
<!-- Especially do not change the two lines below -->The versions of these packages can be found below: