Update app.py

app.py

@@ -1,20 +1,11 @@
 # How to poop like a cat?
 
 import gradio as gr
+# Use a pipeline as a high-level helper
 from transformers import pipeline
 
-pipeline = pipeline(task="image-classification", model="mistralai/Mistral-Nemo-Instruct-2407")
-
-def predict(input_img):
-    predictions = pipeline(input_img)
-    return input_img, {p["label"]: p["score"] for p in predictions} 
-
-gradio_app = gr.Interface(
-    predict,
-    inputs=gr.Image(label="Select hot dog candidate", sources=['upload', 'webcam'], type="pil"),
-    outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
-    title="Hot Dog? Or Not?",
-)
-
-if __name__ == "__main__":
-    gradio_app.launch()
+pipe = pipeline("text-generation", model="mistralai/Mistral-Nemo-Instruct-2407")
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe(messages)