Update app.py

app.py

@@ -250,6 +250,7 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
             st = time.time()
             pipe.unfuse_lora()
             pipe.unload_lora_weights()
+            pipe.unload_textual_inversion()
             et = time.time()
             elapsed_time = et - st
             print('Unfuse and unload LoRA took: ', elapsed_time, 'seconds')
@@ -266,15 +267,9 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
             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(embedding_path)
-            try:
-                pipe.unload_textual_inversion()
-                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)
-            except:
-                pipe.unload_textual_inversion()
-                pipe.load_textual_inversion(state_dict_embedding["text_encoders_0"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
-                pipe.load_textual_inversion(state_dict_embedding["text_encoders_1"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
-
+            pipe.load_textual_inversion(state_dict_embedding["clip_l" if "clip_l" in state_dict_embedding else "text_encoders_0"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
+            pipe.load_textual_inversion(state_dict_embedding["clip_g" if "clip_g" in state_dict_embedding else "text_encoders_1"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
+            
     print("Processing prompt...")
     st = time.time()
     conditioning, pooled = compel(prompt)