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| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium") | |
| model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium") | |
| chat_history_ids = None | |
| def chat(user_input): | |
| global chat_history_ids | |
| new_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt') | |
| bot_input_ids = torch.cat([chat_history_ids, new_input_ids], dim=-1) if chat_history_ids is not None else new_input_ids | |
| chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id) | |
| response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True) | |
| return response | |
| gr.Interface(fn=chat, inputs="text", outputs="text", title="🤖 NetherMite Chatbot").launch() | |