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