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Modulus Checkpoints: CorrDiff

Logo for Modulus Checkpoints: CorrDiff
Pre-trained CorrDiff checkpoints with a sample dataset
Latest Version
April 10, 2024
683.9 MB

CorrDiff Inference Package

This package provides the pre-trained CorrDiff checkpoints for Taiwan, as well as a small dataset sample to easily explore the inference capabilities. This checkpoint was trained on ERA5 → WRF data that spans 2018-2021 at one hour time resolution.

Getting started

Follow these steps to set up all needed to run the CorrDiff inference:

  1. Clone the NVIDIA Modulus package, check out a specific hash, and install it:
git clone
cd modulus
git checkout ee6b3ac0d4c32bca1c81f401d2bfd461887eb9a3
pip install .
  1. Get this package using direct download or via wget:
wget --content-disposition -O
  1. Unzip the contents in the same directory:
  1. Assuming you have both the Modulus and the unzipped CorrDiff inference packages in the <root_dir> directory, go to the directory that includes the CorrDiff inference script:
cd <root_dir>/modulus/examples/generative/corrdiff
  1. Run the inference:
python dataset.data_path=<root_dir>/corrdiff_inference_package/dataset/2023-01-24-cwb-4years_5times.zarr res_ckpt_filename=<root_dir>/corrdiff_inference_package/checkpoints/diffusion.mdlus reg_ckpt_filename=<root_dir>/corrdiff_inference_package/checkpoints/regression.mdlus seed_batch_size=5 use_torch_compile=false


The checkpoints are distributed under the Apache 2.0 license, and the sample dataset is distributed under the CC BY-NC-ND 4.0 license.