Update app.py

app.py

@@ -1,4 +1,4 @@
-
+import torch
 from transformers import VisionEncoderDecoderModel, ViTFeatureExtractor, AutoTokenizer
 
 model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
@@ -32,5 +32,6 @@ def predict_step(image_paths):
   preds = [pred.strip() for pred in preds]
   return preds
 
+torch.hub.download_url_to_file('https://github.com/AaronCWacker/Yggdrasil/blob/main/images/35-Favorite-Games.jpg?raw=true', '35-Favorite-Games.jpg')
 
-predict_step(['doctor.e16ba4e4.jpg'] # ['a woman in a hospital bed with a woman in a hospital bed']
+predict_step(['35-Favorite-Games.jpg'] # ['a woman in a hospital bed with a woman in a hospital bed']