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import gradio as gr
from transformers import pipeline
# Load your fine-tuned model from the Hub
chatbot = pipeline(
"text2text-generation",
model="abinashnp/bayedger-chatbot", # or your fine-tuned model ID
tokenizer="abinashnp/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()
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