Update app.py

app.py

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