Update app.py

app.py

@@ -11,7 +11,7 @@ from engine import inference
 
 
 model_trained = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-model_trained.load_state_dict(torch.load('model_trained.pth',map_location=torch.device('cpu')))
+model_trained.load_state_dict(torch.load('model_trained.pth',map_location=torch.device('cpu')),strict=False)
 image_processor = ViTImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
 tokenizer       = GPT2TokenizerFast.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
 
@@ -38,12 +38,12 @@ prefix_length = 10
 
 model = ClipCaptionModel(prefix_length)
 
-model.load_state_dict(torch.load('model.h5',map_location=torch.device('cpu'))) 
+model.load_state_dict(torch.load('model.h5',map_location=torch.device('cpu')),strict=False) 
 
 model = model.eval() 
 
 coco_model = ClipCaptionModel(prefix_length)
-coco_model.load_state_dict(torch.load('COCO_model.h5',map_location=torch.device('cpu')))
+coco_model.load_state_dict(torch.load('COCO_model.h5',map_location=torch.device('cpu')),strict=False)
 # model = model.eval()