Update app.py

app.py

@@ -3,7 +3,7 @@ import spaces
 
 import torch
 torch.jit.script = lambda f: f
-torch.autocast = lambda device_type, dtype: lambda f: f
+# torch.autocast = lambda device_type, dtype: lambda f: f
 
 from t2v_metrics import VQAScore, list_all_vqascore_models
 
@@ -11,17 +11,17 @@ 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
-# print("Model initialized!")
+model_pipe = VQAScore(model="clip-flant5-xl")  # our recommended scoring model
+print("Model initialized!")
 
 @spaces.GPU
 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")
+    model_pipe.to("cuda")
     print("Generating!")
     return model_pipe(images=[image], texts=[text])