multimodalart HF staff commited on
Commit
856c9dc
1 Parent(s): 247fbd7

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +1 -0
app.py CHANGED
@@ -257,6 +257,7 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, sdxl_lora
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  if(is_pivotal):
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  #Add the textual inversion embeddings from pivotal tuning models
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  text_embedding_name = sdxl_loras[selected_state.index]["text_embedding_weights"]
 
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  state_dict_embedding = load_file(text_embedding_name)
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  pipe.load_textual_inversion(state_dict_embedding["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
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  pipe.load_textual_inversion(state_dict_embedding["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
 
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  if(is_pivotal):
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  #Add the textual inversion embeddings from pivotal tuning models
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  text_embedding_name = sdxl_loras[selected_state.index]["text_embedding_weights"]
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+ embedding_path = hf_hub_download(repo_id=repo_name, filename=text_embedding_name, repo_type="model")
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  state_dict_embedding = load_file(text_embedding_name)
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  pipe.load_textual_inversion(state_dict_embedding["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
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  pipe.load_textual_inversion(state_dict_embedding["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)