Update README.md

README.md

@@ -1,14 +1,3 @@
----
-tags:
-- fourier-neural-operator
-- seismic
-- structural-engineering
-- time-series
-- regression
-- pytorch
-library_name: pytorch
-pipeline_tag: other
----
 
 # SeFNO — Seismic Floor Acceleration Response Prediction (FNO v1.0+)
 
@@ -79,50 +68,7 @@ pip install -r requirement.txt   # Windows
 
 ### Load a checkpoint and run inference
 
-```python
-import torch
-from neuralop.models import FNO
-
-def load_fno(checkpoint_path, n_modes, hidden_channels, n_layers, device="cuda"):
-    model = FNO(
-        n_modes                  = (n_modes,),
-        hidden_channels          = hidden_channels,
-        in_channels              = 1,
-        out_channels             = 1,
-        n_layers                 = n_layers,
-        projection_channel_ratio = 2,
-        domain_padding           = 0.1,
-    )
-    ckpt  = torch.load(checkpoint_path, map_location=device, weights_only=False)
-    state = ckpt.get("model_state_dict", ckpt)
-    # strip torch.compile prefix if present
-    state = {(k[10:] if k.startswith("_orig_mod.") else k): v for k, v in state.items()}
-    model.load_state_dict(state)
-    return model.to(device).eval()
-
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-# --- Base model ---
-model = load_fno(
-    checkpoint_path = "output/Base-FNO_v1.0+_h64_m64_l4_e50_.../model/fno_best.pth",
-    n_modes         = 64,
-    hidden_channels = 64,
-    n_layers        = 4,
-    device          = device,
-)
-
-# --- Inference on a single ground motion ---
-import numpy as np
-
-gm_array = np.load("my_ground_motion.npy")   # shape (3000,), unit m/s²
-x = torch.from_numpy(gm_array).float().unsqueeze(0).unsqueeze(0).to(device)  # (1,1,3000)
-
-with torch.no_grad():
-    pred = model(x).cpu().numpy().squeeze()   # shape (3000,)
-
-print("Predicted roof acceleration shape:", pred.shape)
-```
+Refer to github repo.
 
 ### Quick review notebook
 
@@ -145,19 +91,6 @@ Open `quick_inference.ipynb` in the cloned repository to run inference on the he
 
 ---
 
-## Citation
-
-If you use these models, please cite (forthcoming):
-
-```
-@misc{jiang2025sefno,
-  title  = {SeismicFNO: Fourier Neural Operators for Seismic Structural Response Prediction},
-  author = {Jason Jiang},
-  year   = {2025},
-  url    = {https://github.com/HKUJasonJiang/Seismic-FNO}
-}
-```
-
 ## License
 
 [Creative Commons Attribution 4.0 (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)