from transformers import AutoModelForCausalLM, AutoTokenizer from transformers import BlenderbotForConditionalGeneration import torch import gradio as gr # model_name = "facebook/blenderbot-400M-distill" model_name = "microsoft/DialoGPT-medium" chat_tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name) def conversation(user_input, chat_history=[]): user_input_ids = chat_tokenizer(user_input+chat_tokenizer.eos_token, return_tensors="pt").input_ids # maintain history in the tensor chatbot_input_ids = torch.cat([torch.LongTensor(chat_hostory), user_input_ids], dim=-1) # ger response chat_history = model.generate(chatbot_input_ids, max_length=1000, pad_token_id=chat_tokenizer.eos_token_id).tolist() print(chat_history) response = chat_tokeniser.decode(chat_history[0]).split("<|endoftext|>") print("Starting to print response") print(response) # html for display html = "