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import torch |
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from safetensors.torch import save_file, load_file |
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import gradio as gr |
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import os |
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def convert_embedding(uploaded_file): |
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output_path = "embedding.safetensors" |
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file_extension = os.path.splitext(uploaded_file.name)[1] |
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if file_extension == '.pt': |
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sd15_embedding = torch.load(uploaded_file.name, map_location=torch.device('cpu'), weights_only=True) |
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sd15_tensor = sd15_embedding['string_to_param']['*'] |
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elif file_extension == '.safetensors': |
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loaded_tensors = load_file(uploaded_file.name) |
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sd15_tensor = loaded_tensors['emb_params'] |
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else: |
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raise ValueError("Unsupported file format") |
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num_vectors = sd15_tensor.shape[0] |
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clip_g_shape = (num_vectors, 1280) |
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clip_l_shape = (num_vectors, 768) |
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clip_g = torch.zeros(clip_g_shape, dtype=torch.float16) |
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clip_l = torch.zeros(clip_l_shape, dtype=torch.float16) |
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clip_l[:sd15_tensor.shape[0], :sd15_tensor.shape[1]] = sd15_tensor.to(dtype=torch.float16) |
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save_file({"clip_g": clip_g, "clip_l": clip_l}, output_path) |
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return output_path |
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iface = gr.Interface( |
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fn=convert_embedding, |
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inputs=gr.File(label="Upload SD1.5 embedding"), |
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outputs=gr.File(label="Download converted SDXL safetensors embedding"), |
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title="SD1.5 to SDXL Embedding Converter", |
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description="Upload an SD1.5 embedding file to convert it to SDXL." |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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