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yyiming3/gencast_distillation

sourceHugging Facecc-by-nc-sa-4.0updated 1mo agoView on Hugging Face

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GenCast Distillation

GenCast Distillation is a single-step probabilistic weather forecasting model distilled from the multi-step Google DeepMind GenCast diffusion model.

Model file

Checkpoint format:

—Framework: JAX / Haiku
—Format: Google DeepMind GenCast-compatible CheckPoint NPZ
—Resolution: 1 degree
—Pressure levels: 13
—Parameters: distilled EMA student
—SHA256: fa5d5bb970f3650cec25857eecea58529b74b3ba6a69ce9765637d2be9173247

Base model

The student was distilled from:

—Model: GenCast 1p0deg <2019
—Developer: Google DeepMind
—Source: gs://dm_graphcast/gencast/params/GenCast 1p0deg <2019.npz
—Repository: https://github.com/google-deepmind/weathernext

The original GenCast model weights are distributed under CC BY-NC-SA 4.0.

Evaluation

The model is evaluated on:

Global Weather Forecasting

Global ensemble forecasting evaluated with WeatherBench2.

Typhoon Prediction

Typhoon-track prediction evaluated against IBTrACS, with optional TempestExtremes tracking and lead-time-dependent position-error analysis.

Usage

bash

hf download yyiming3/GenCast-Distillation \
  student_gencast_dm.npz \
  --local-dir /path/to/weights

git clone https://github.com/yyimingucl/gencast_distillation
cd genCast_distillation
conda env create -f environment.yaml
conda activate dmd_gencast

DATA_DIR=/path/to/data
MODEL_CHECKPOINT_PATH=/path/to/weights/student_gencast_dm.npz

bash long_run_js/eval_gwf.sh