Add Safetensor Conversion Script + Safetensor File

checkpoints/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9bbcbf73561f6bc5d0a17ea6a2081feed2d1304e87602d8c502d9a5c4bd85576
+size 16

convert_to_safetensors.py

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+import os
+import torch
+from safetensors.torch import save_file
+import glob
+
+def convert_model_to_safetensors(model_path, output_path):
+    print(f"Looking for PyTorch model files in {model_path}")
+    
+    # Create the output directory if it doesn't exist
+    os.makedirs(os.path.dirname(output_path), exist_ok=True)
+    
+    # Load the PyTorch model file
+    model_files = glob.glob(os.path.join(model_path, "*.pt")) + \
+                 glob.glob(os.path.join(model_path, "*.pth")) + \
+                 glob.glob(os.path.join(model_path, "pytorch_model.bin"))
+    
+    if not model_files:
+        raise FileNotFoundError(f"No PyTorch model files found in {model_path}")
+    
+    print(f"Found model file(s): {model_files}")
+    model_file = model_files[0]  # Use the first found model file
+    
+    # Load the state dict
+    print(f"Loading model from {model_file}")
+    checkpoint = torch.load(model_file, map_location='cpu')
+    
+    # Extract only the model weights, removing metadata
+    model_state_dict = {}
+    if isinstance(checkpoint, dict):
+        if 'state_dict' in checkpoint:
+            checkpoint = checkpoint['state_dict']
+        # Only keep tensor values
+        for key, value in checkpoint.items():
+            if isinstance(value, torch.Tensor):
+                model_state_dict[key] = value
+    
+    # Save as safetensors
+    print(f"Converting to safetensors and saving to {output_path}")
+    save_file(model_state_dict, output_path)
+    print("Conversion completed successfully!")
+
+if __name__ == "__main__":
+    # Update these paths according to your model location
+    model_path = "./checkpoints"  # Path to your checkpoints directory
+    output_path = "./checkpoints/model.safetensors"
+    
+    convert_model_to_safetensors(model_path, output_path)