BGLab
/

DeepONet-FlowBench-FPO

Time Series Forecasting

pytorch-lightning

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arabeh commited on 14 days ago

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@@ -22,7 +22,7 @@ These models are trained on the **FlowBench FPO** data and learn to predict unst
 - **Paper page on Hugging Face:** https://huggingface.co/papers/2512.04434
 - **Dataset (FlowBench on Hugging Face):** https://huggingface.co/datasets/BGLab/FlowBench
 - **Code (model implementation & training scripts):** https://github.com/baskargroup/TimeDependent-DeepONet
-- **Interactive demo (Hugging Face Space):** https://huggingface.co/spaces/arabeh/DeepONet-FPO-demo
 ---
@@ -45,7 +45,7 @@ import torch
 from models.geometric_deeponet.geometric_deeponet import GeometricDeepONetTime
-REPO_ID = "arabeh/DeepONet-FlowBench-FPO"
 filename = "checkpoints/time-dependent-deeponet_4in.ckpt"  # choose 1in / 4in / 8in / 16in
 # 1) Download checkpoint file locally

 - **Paper page on Hugging Face:** https://huggingface.co/papers/2512.04434
 - **Dataset (FlowBench on Hugging Face):** https://huggingface.co/datasets/BGLab/FlowBench
 - **Code (model implementation & training scripts):** https://github.com/baskargroup/TimeDependent-DeepONet
+- **Interactive demo (Hugging Face Space):** https://huggingface.co/spaces/BGLab/DeepONet-FPO-demo
 ---
 from models.geometric_deeponet.geometric_deeponet import GeometricDeepONetTime
+REPO_ID = "BGLab/DeepONet-FlowBench-FPO"
 filename = "checkpoints/time-dependent-deeponet_4in.ckpt"  # choose 1in / 4in / 8in / 16in
 # 1) Download checkpoint file locally