Update app.py

app.py

@@ -2,22 +2,15 @@ import os
 import gradio as gr
 import torch
 import PIL
-import transformers
-transformers.utils.move_cache()
 
 from flamingo_mini import FlamingoConfig, FlamingoModel, FlamingoProcessor
 
-
-
 EXAMPLES_DIR = 'examples'
 DEFAULT_PROMPT = "<image>"
-
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-
 model = FlamingoModel.from_pretrained('dhansmair/flamingo-mini')
 model.to(device)
 model.eval()
-
 processor = FlamingoProcessor(model.config, load_vision_processor=True)
 
 # setup some example images
@@ -27,21 +20,16 @@ if os.path.isdir(EXAMPLES_DIR):
         path = EXAMPLES_DIR + "/" + file
         examples.append([path, DEFAULT_PROMPT])
 
-
 def predict_caption(image, prompt):
     assert isinstance(prompt, str)
-    
     features = processor.extract_features(image).to(device)
     caption = model.generate_captions(processor, 
             visual_features=features,
             prompt=prompt)
-  
     if isinstance(caption, list):
         caption = caption[0]
-    
     return caption
-
-
+    
 iface = gr.Interface(fn=predict_caption, 
         inputs=[gr.Image(type="pil"), gr.Textbox(value=DEFAULT_PROMPT, label="Prompt")], 
         examples=examples,