Update app.py

app.py

@@ -11,7 +11,7 @@ print(list_all_vqascore_models())
 
 # Initialize the model only once
 # if torch.cuda.is_available(): 
-model_pipe = VQAScore(model="clip-flant5-xl", device="cpu")  # our recommended scoring model
+# model_pipe = VQAScore(model="clip-flant5-xl", device="cpu")  # our recommended scoring model
 print("Model initialized!")
 
 @spaces.GPU
@@ -19,15 +19,15 @@ def generate(model_name, image, text):
     # print("Model_name:", model_name)
     print("Image:", image)
     print("Text:", text)
-    # model_pipe = VQAScore(model="clip-flant5-xl")  # our recommended scoring model
+    model_pipe = VQAScore(model="clip-flant5-xl")  # our recommended scoring model
     # print("Model initialized, now moving to cuda")
     # model_pipe.to("cuda")
     print("Generating!")
     # with torch.autocast(device_type='cuda'):
-    # with torch.autocast(device_type='cuda', dtype=torch.float):
-    #     result = model_pipe(images=[image], texts=[text])
-    #     return result
-    return 10
+    with torch.autocast(device_type='cuda', dtype=torch.float):
+        result = model_pipe(images=[image], texts=[text])
+        return result
+    # return 10
 
 iface = gr.Interface(
     fn=generate,  # function to call