Fix (#1)

- Fix (28ed6816a78dd70c0548e027d85e8a503b9e688b)


Co-authored-by: hysts <hysts@users.noreply.huggingface.co>

app.py

@@ -4,7 +4,7 @@ from PIL import Image
 from diffusers import AutoPipelineForText2Image, DDIMScheduler
 from transformers import CLIPVisionModelWithProjection
 import numpy as np
-import spaces 
+import spaces
 
 
 image_encoder = CLIPVisionModelWithProjection.from_pretrained(
@@ -25,7 +25,7 @@ pipeline.set_ip_adapter_scale([0.7, 0.5])
 
 pipeline.enable_model_cpu_offload()
 
-@spaces.ZeroGPU  
+@spaces.GPU
 def transform_image(face_image):
     generator = torch.Generator(device="cpu").manual_seed(0)
 
@@ -39,7 +39,7 @@ def transform_image(face_image):
         raise ValueError("Unsupported image format")
 
     # Load the style image from the local path
-    style_image_path = "/content/soyjak2.jpeg"
+    style_image_path = "examples/soyjak2.jpg"
     style_image = Image.open(style_image_path)
 
     # Perform the transformation
@@ -63,4 +63,4 @@ demo = gr.Interface(
 )
 
 demo.queue(max_size=20)  # Configures the queue with a maximum size of 20
-demo.launch()
+demo.launch()