Update app.py

app.py

@@ -2,4 +2,22 @@ from transformers import ViTFeatureExtractor, ViTModel
 from PIL import Image
 import requests
 
-runaksh/chest_xray_pneumonia_detection
+loaded_model = AutoModelForSequenceClassification.from_pretrained("runaksh/chest_xray_pneumonia_detection")
+
+pipe = pipeline('image-classification', model=model_name, device=0)
+
+# Create title, description and article strings
+title = "Classification Demo"
+description = "XRay classification"
+
+# Create the Gradio demo
+demo = gr.Interface(fn=pipe, # mapping function from input to output
+                    inputs=gr.Image(type='filepath'), # what are the inputs?
+                    outputs=[gr.Label(label="Predictions"), # what are the outputs?
+                             gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
+                    examples=example_list,
+                    title=title,
+                    description=description,)
+
+# Launch the demo!
+demo.launch()