app.py

import gradio as gr
from transformers import pipeline

# Load your fine-tuned model from the Hub
chatbot = pipeline(
    "text2text-generation",
    model="your-username/bayedger-chatbot",  # or your fine-tuned model ID
    tokenizer="your-username/bayedger-chatbot",
)

def respond(query):
    # generate response
    out = chatbot(f"question: {query} answer:",
                  max_new_tokens=150,
                  temperature=1.0,
                  top_p=0.9,
                  repetition_penalty=1.1,
                  num_beams=1)[0]["generated_text"]
    return out

# Build Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# 🤖 Bayedger FAQ Chatbot")
    txt = gr.Textbox(label="Ask me anything", placeholder="Type your question here…")
    out = gr.Textbox(label="Answer")
    txt.submit(respond, txt, out)

demo.launch()