Update app.py

app.py

@@ -186,9 +186,9 @@ class StableDiffusionPipeline:
         return image, image_vae
 
 # Load models (adjust the paths to your model directories)
-vae = AutoencoderKL.from_pretrained("Yesianrohn/TextSSR/vae")
-unet = UNet2DConditionModel.from_pretrained("Yesianrohn/TextSSR/unet")
-noise_scheduler = DDPMScheduler.from_pretrained("Yesianrohn/TextSSR/scheduler")
+vae = AutoencoderKL.from_pretrained("Yesianrohn/TextSSR", subfolder="vae")
+unet = UNet2DConditionModel.from_pretrained("Yesianrohn/TextSSR", subfolder="unet")
+noise_scheduler = DDPMScheduler.from_pretrained("Yesianrohn/TextSSR", subfolder="scheduler")
 
 # Create pipeline
 pipe = StableDiffusionPipeline(vae=vae, unet=unet, scheduler=noise_scheduler, device=device)