Update app.py

app.py

@@ -5,9 +5,9 @@ from transformers import AutoTokenizer, ViTImageProcessor, VisionEncoderDecoderM
 device = 'cpu'
 
 # Load the pretrained model, feature extractor, and tokenizer
-model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning").to(device)
-feature_extractor = ViTImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
+model = VisionEncoderDecoderModel.from_pretrained("premanthcharan/Image_Captioning_Model").to(device)
+feature_extractor = ViTImageProcessor.from_pretrained("premanthcharan/Image_Captioning_Model")
+tokenizer = AutoTokenizer.from_pretrained("premanthcharan/Image_Captioning_Model")
 
 def predict(image, max_length=64, num_beams=4):
     # Process the input image