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from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import gradio as gr
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
def predict(input, history=[]):
new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
history = model.generate(bot_input_ids, max_length=500, pad_token_id=tokenizer.eos_token_id).tolist()
response = tokenizer.decode(history[0]).replace("<|endoftext|>", "\n")
return response, history
gr.Interface(fn=predict, title="DialoGPT-large", inputs=[gr.inputs.Textbox(placeholder="Write a text message as if writing a text message to a human."), "state"], outputs=[gr.outputs.Textbox(label="Output"), "state"]).launch() |