llama2

app.py

@@ -1,15 +1,13 @@
 import gradio as gr
 from transformers import pipeline
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+pipeline = pipeline(task="text-generation", model="meta-llama/Llama-2-7b")
 
-def predict(image):
-    predictions = pipeline(image)
-    return {p["label"]: p["score"] for p in predictions}
+def predict(input):
+    return pipeline("I can't believe you did such a ", do_sample=False)
 
 gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
+    fn=predict,
+    inputs=gr.Textbox(lines=2, placeholder="Text here..."),
+    outputs="text",
 ).launch()