Update README.md

README.md

@@ -48,6 +48,39 @@ wsi_dataset = load_dataset("Lab-Rasool/TCGA", "wsi", split="train")
 molecular_dataset = load_dataset("Lab-Rasool/TCGA", "molecular", split="train")
 ```
 
+Example code for loading HF dataset into a PyTorch Dataloader.
+**Note**: Some embeddings are stored as buffers due to their multi-dimensional shape.
+
+```python
+from datasets import load_dataset
+import os
+from torch.utils.data import Dataset
+import numpy as np
+
+class CustomDataset(Dataset):
+    def __init__(self, hf_dataset):
+        self.hf_dataset = hf_dataset
+
+    def __len__(self):
+        return len(self.hf_dataset)
+    
+    def __getitem__(self, idx):
+        hf_item = self.hf_dataset[idx]
+        embedding = np.frombuffer(hf_item["embedding"], dtype=np.float32)
+        embedding_shape = hf_item["embedding_shape"]
+        embedding = embedding.reshape(embedding_shape)
+        return embedding
+
+if __name__ == "__main__":
+    
+    clinical_dataset = load_dataset("Lab-Rasool/TCGA", "clinical", split="train")
+    wsi_dataset = load_dataset("Lab-Rasool/TCGA", "wsi", split="train")
+    
+    for index, item in enumerate(clinical_dataset):
+        print(np.frombuffer(item.get("embedding"), dtype=np.float32).reshape(item.get("embedding_shape")).shape)
+        break
+```
+
 ## Dataset Creation
 
 #### Data Collection and Processing