import gradio as gr from transformers import AutoModelForCausalLM, AutoTokenizer import torch title = "Ask Rick a Question" description = """
The bot was trained to answer questions based on Rick and Morty dialogues. Ask Rick anything!
""" article = "Check out [the original Rick and Morty Bot](https://huggingface.co/spaces/kingabzpro/Rick_and_Morty_Bot) that this demo is based off of." tokenizer = AutoTokenizer.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2") model = AutoModelForCausalLM.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2") def predict(input): # tokenize the new input sentence new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') # generate a response history = model.generate(new_user_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist() # convert the tokens to text, and then split the responses into the right format response = tokenizer.decode(history[0]).split("<|endoftext|>") return response[1] gr.Interface(fn = predict, inputs = ["textbox"], outputs = ["text"], title = title, description = description, article = article).launch()