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import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
def main():
model_name = "microsoft/DialoGPT-small"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
print("Type 'quit' to exit.")
chat_history_ids = None
for step in range(20):
user = input("You: ").strip()
if user.lower() == "quit":
break
new_user_input_ids = tokenizer.encode(user + tokenizer.eos_token, return_tensors="pt").to(device)
bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if chat_history_ids is not None else new_user_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)
print("Bot:", response)
if __name__ == "__main__":
main()
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