Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the model
+pipe = pipeline("text-generation", model="defog/llama-3-sqlcoder-8b")
+
+# Define a function that will take user input and generate text
+def generate_response(user_input):
+    messages = [{"role": "user", "content": user_input}]
+    result = pipe(messages)
+    return result[0]['generated_text']
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=generate_response,  # The function to call for generating responses
+    inputs="text",         # The type of input: a text box
+    outputs="text",        # The type of output: a text box
+    title="Text Generation with LLaMA-3",
+    description="Ask anything!"
+)
+
+# Launch the app
+iface.launch()