app.py

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import gradio as gr

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("gpt-chatbot")
model = AutoModelForCausalLM.from_pretrained("gpt-chatbot")


def generate_response(input_text):
    input_ids = tokenizer.encode(input_text + " >> User: ", return_tensors='pt')
    generated_output = model.generate(input_ids, max_length=100, num_return_sequences=1)
    response = tokenizer.decode(generated_output[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
    return response

iface = gr.Interface(
    fn=generate_response,
    inputs='text',
    outputs='text',
    layout='vertical',
    title='ChatGPT',
    description='A simple chatbot powered by ChatGPT',
    article= 'https://huggingface.co/models',
    examples=[['Hello'], ['How are you?'], ['What is your name?']],
)

iface.launch(share=True)