Added new merged safetensors files

MergeSafetensors.py

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+from safetensors.torch import save_file, load_file
+import torch
+
+def merge_model_components(
+    unet_path,
+    vae_path,
+    text_encoder_path,
+    output_path
+):
+    """
+    Merge UNet, VAE, and text encoder into a single safetensors file.
+    
+    Args:
+        unet_path: Path to the main model/unet safetensors file
+        vae_path: Path to the VAE safetensors file
+        text_encoder_path: Path to the text encoder/CLIP safetensors file
+        output_path: Path where the merged file will be saved
+    """
+    
+    print("Loading UNet/Model weights...")
+    unet_state = load_file(unet_path)
+    
+    print("Loading VAE weights...")
+    vae_state = load_file(vae_path)
+    
+    print("Loading Text Encoder weights...")
+    text_encoder_state = load_file(text_encoder_path)
+    
+    # Merge all state dictionaries
+    print("Merging state dictionaries...")
+    merged_state = {}
+    
+    # Add all UNet weights
+    merged_state.update(unet_state)
+    
+    # Add VAE weights with proper prefixes if needed
+    for key, value in vae_state.items():
+        # If keys don't already have 'vae.' prefix, add it
+        if not key.startswith('vae.'):
+            merged_state[f'vae.{key}'] = value
+        else:
+            merged_state[key] = value
+    
+    # Add text encoder weights with proper prefixes
+    for key, value in text_encoder_state.items():
+        # If keys don't already have 'text_encoder.' prefix, add it
+        if not key.startswith('text_encoder.'):
+            merged_state[f'text_encoder.{key}'] = value
+        else:
+            merged_state[key] = value
+    
+    print(f"Total parameters in merged model: {len(merged_state)}")
+    print(f"Saving merged model to {output_path}...")
+    
+    # Save the merged state dictionary
+    save_file(merged_state, output_path)
+    
+    print("✅ Merge complete!")
+    print(f"File saved to: {output_path}")
+    
+    # Print file size
+    import os
+    size_gb = os.path.getsize(output_path) / (1024**3)
+    print(f"File size: {size_gb:.2f} GB")
+
+
+# Example usage
+if __name__ == "__main__":
+    merge_model_components(
+        unet_path="svdq-fp4_r32-flux.1-depth-dev.safetensors",
+        vae_path="vae/diffusion_pytorch_model.safetensors", 
+        text_encoder_path="text_encoder/model.safetensors",
+        output_path="flux1-depth-dev_fp4_merged_model.safetensors"
+    )

flux1-depth-dev_fp4_merged_model.safetensors

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+oid sha256:44d0a7a1c2353131a545f3a62ceff6a5affa2b5cfcc28f334a075bb58df8819b
+size 7866673892

svdq-fp4_r32-flux.1-depth-dev.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4df7e844b18c35e003b906c5690894529b1f9ccccb2b32977948461f1db45d2a
+size 7039100192