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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import gradio as gr
model_name = "microsoft/Phi-4-mini-instruct"
# Load model & tokenizer with optimizations
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
# Create a pipeline for text generation (faster inference)
chatbot = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=200)
def chatbot_response(user_input):
response = chatbot(user_input)[0]["generated_text"]
return response
# Gradio UI
iface = gr.Interface(
fn=chatbot_response,
inputs="text",
outputs="text",
title="Ethical AI Chatbot",
description="A chatbot for ethical AI guidance."
)
iface.launch()
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