Create app.py

app.py

@@ -0,0 +1,28 @@
+# main.py
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+# Load model and tokenizer
+model_name = "llama-2-7b-chat"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+chat_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Define the generate_response function
+def generate_response(prompt):
+    response = chat_pipeline(prompt, max_length=50)[0]['generated_text']
+    return response
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    layout="vertical",
+    title="LLAMA-2-7B Chatbot",
+    description="Enter a prompt and get a chatbot response.",
+    examples=[["Tell me a joke."]],
+)
+
+if __name__ == "__main__":
+    interface.launch()