Spaces:
Running
Running
| 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() |