Update app.py

app.py

@@ -54,21 +54,21 @@ else:
     placeholder_token_id = pipe.tokenizer.convert_tokens_to_ids(placeholder_token)
     pipe.text_encoder.get_input_embeddings().weight.data[placeholder_token_id] = embeddings
 
-embeddings_path=hf_hub_download(repo_id=model_id, filename="embeddings/positive/embellish2.pt", use_auth_token=auth_token)
+embeddings_path=hf_hub_download(repo_id=model_id, filename="embeddings/positive/embellish1.pt", use_auth_token=auth_token)
 embeddings_dict=torch.load(embeddings_path)
 print(embeddings_dict)
 if "string_to_param" in embeddings_dict:
     embeddings = next(iter(embeddings_dict['string_to_param'].values()))
-    embellish2 = ""
+    embellish1 = ""
     for i, emb in enumerate(embeddings):
         token = f"kskd{chr(i%26+65)}{chr(i//26+65)}"
-        embellish2 += token
+        embellish1 += token
         pipe.tokenizer.add_tokens(token)
         pipe.text_encoder.resize_token_embeddings(len(pipe.tokenizer))
         token_id = pipe.tokenizer.convert_tokens_to_ids(token)
         pipe.text_encoder.get_input_embeddings().weight.data[token_id] = emb
 else:
-    embellish2 = list(embeddings_dict.keys())[0]
+    embellish1 = list(embeddings_dict.keys())[0]
     embeddings = embeddings_dict[embellish2].to(pipe.text_encoder.get_input_embeddings().weight.dtype)
     pipe.tokenizer.add_tokens(placeholder_token)
     pipe.text_encoder.resize_token_embeddings(len(pipe.tokenizer))
@@ -118,7 +118,7 @@ def auto_prompt_correction(prompt_ui,neg_prompt_ui,disable_auto_prompt_correctio
     if(image_style=="Animetic"):
         style="anime"
     else:
-        style=f"anime,{embellish2}"
+        style=f"anime,{embellish1}"
     
     if(disable_auto_prompt_correction):
         prompt=f"{style}, {prompt}"