Update app.py

app.py

@@ -11,7 +11,7 @@ from PIL import Image
 
 
 MODEL_REPO = 'OFA-Sys/small-stable-diffusion-v0'
-LoRa_DIR = 'weights'
+LoRa_DIR = 'weights/'
 DATASET_REPO = 'VESSL/Bored_Ape_NFT_text'
 SAMPLE_IMAGE = 'weights/Sample.png'
 
@@ -26,7 +26,7 @@ def load_pipeline_w_lora() :
 
     # Load LoRa attn layer weights to unet attn layers
     unet.load_attn_procs(LoRa_DIR)
-    print('loaded')
+    print('LoRa layers loaded')
     
     # Load pipeline
     pipeline = DiffusionPipeline.from_pretrained(
@@ -58,6 +58,7 @@ def main():
     device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
 
     elapsed, pipeline = elapsed_time(load_pipeline_w_lora)
+
     st.write(f"Model is loaded in {elapsed} seconds!")
     
     pipeline = pipeline.to(device)