Upload model.py with huggingface_hub

model.py

@@ -354,44 +354,19 @@ class BT4(nn.Module):
         is_hf_hub = "/" in pretrained_model_name_or_path and not os.path.isdir(pretrained_model_name_or_path)
         
         if is_hf_hub:
-            # Download from HuggingFace Hub - try safetensors first
-            print("DEBUG: Downloading safetensors from HuggingFace...")
+            # Download from HuggingFace Hub
             safetensors_path = hf_hub_download(
                 repo_id=pretrained_model_name_or_path,
                 filename="model.safetensors",
                 cache_dir=kwargs.get("cache_dir", None),
                 token=kwargs.get("token", None),
             )
-            print(f"DEBUG: Loaded safetensors from {safetensors_path}")
             state_dict = load_file(safetensors_path)
-            print(f"DEBUG: State dict has {len(state_dict)} keys")
-            
-            # Debug: check embedding weight before loading
-            embedding_before = model.embedding.weight.sum().item()
-            expected_embedding = state_dict['embedding.weight'].sum().item()
-            print(f"DEBUG: Before loading - embedding: {embedding_before:.6f}, expected: {expected_embedding:.6f}")
-            
             missing_keys, unexpected_keys = model.load_state_dict(state_dict, strict=False)
-            print(f"DEBUG: load_state_dict returned - missing: {len(missing_keys)}, unexpected: {len(unexpected_keys)}")
-            
-            # Debug: check embedding weight after loading
-            embedding_after = model.embedding.weight.sum().item()
-            print(f"DEBUG: After loading - embedding: {embedding_after:.6f}")
-            
             if missing_keys:
                 print(f"Warning: Missing keys when loading weights: {len(missing_keys)} keys")
             if unexpected_keys:
                 print(f"Warning: Unexpected keys when loading weights: {len(unexpected_keys)} keys")
-            
-            # Verify weights loaded
-            if abs(embedding_after - expected_embedding) > 1e-5:
-                print(f"ERROR: Weights did not load correctly!")
-                print(f"  Before: {embedding_before:.6f}, Expected: {expected_embedding:.6f}, After: {embedding_after:.6f}")
-                # Force reload
-                print("DEBUG: Attempting to reload weights...")
-                model.load_state_dict(state_dict, strict=False)
-                embedding_after2 = model.embedding.weight.sum().item()
-                print(f"  After reload: {embedding_after2:.6f}")
         else:
             # Local path - try safetensors first
             safetensors_path = os.path.join(pretrained_model_name_or_path, "model.safetensors")