ai-models-panguweather-gfs


Nameai-models-panguweather-gfs JSON
Version 0.0.7 PyPI version JSON
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home_pagehttps://github.com/jacob-radford/ai-models-panguweather-gfs
SummaryRun panguweather with capabilities for GFS and GDAS initial conditions and NetCDF output
upload_time2024-07-26 02:21:54
maintainerNone
docs_urlNone
authorJacob Radford
requires_pythonNone
licenseApache License Version 2.0
keywords tool
VCS
bugtrack_url
requirements No requirements were recorded.
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coveralls test coverage No coveralls.
            # ai-models-panguweather-gfs

`ai-models-panguweather-gfs` is an extension of the [ai-models-panguweather](https://github.com/ecmwf-lab/ai-models-panguweather) package, which itself is a plugin to run [Huawei's Pangu-Weather](https://github.com/198808xc/Pangu-Weather) with [i-models](https://github.com/ecmwf-lab/ai-models).

Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast, arXiv preprint: 2211.02556, 2022.
<https://arxiv.org/abs/2211.02556>

Pangu-Weather was created by Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu and Qi Tian. It is released by Huawei Cloud.

The trained parameters of Pangu-Weather are made available under the terms of the BY-NC-SA 4.0 license.

The commercial use of these models is forbidden.

See <https://github.com/198808xc/Pangu-Weather> for further details.

### Installation

To install the package, run:

```bash
pip install ai-models-panguweather-gfs
```

This will install the package and its dependencies, in particular the ONNX runtime. The installation script will attempt to guess which runtime to install. You can force a given runtime by specifying the the `ONNXRUNTIME` variable, e.g.:

```bash
ONNXRUNTIME=onnxruntime-gpu pip install ai-models-panguweather-gfs
```

            

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