Update app.py

app.py

@@ -23,6 +23,7 @@ unet = pipe.unet
 lora_path = hf_hub_download(repo_id="SvenN/sdxl-emoji", filename="lora.safetensors", repo_type="model")
 embeddings_path = hf_hub_download(repo_id="SvenN/sdxl-emoji", filename="embeddings.pti", repo_type="model")
 
+#### Loading LoRA keys into the UNet #### 
 tensors = load_file(lora_path)
 unet_lora_attn_procs = {}
 name_rank_map = {}
@@ -60,11 +61,14 @@ for name, attn_processor in unet.attn_processors.items():
 
 unet.set_attn_processor(unet_lora_attn_procs)
 unet.load_state_dict(tensors, strict=False)
+#### End loading LoRA keys into the UNet 
 
+### Start loading Embeddings into the text encoder ### 
 handler = TokenEmbeddingsHandler(
     [pipe.text_encoder, pipe.text_encoder_2], [pipe.tokenizer, pipe.tokenizer_2]
 )
 handler.load_embeddings(embeddings_path)
+### End loading embeddings into the text encoder ### 
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024