added processors

app.py

@@ -7,6 +7,8 @@ client = Groq(
     api_key="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",
 )
 
+model_id = 'google/vit-base-patch16-224'
+
 # Streamlit app title
 st.title("Product Detection App")
 
@@ -15,7 +17,8 @@ uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png
 
 if uploaded_file is not None:
     image = Image.open(uploaded_file)
-
+    processor = ViTImageProcessor.from_pretrained(model_id)
+    model = ViTForImageClassification.from_pretrained(model_id)
     # Process the image and make predictions
     inputs = processor(images=image, return_tensors="pt")
     outputs = model(**inputs)