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Create README.md

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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Ahmade/rick-and-morty-v2")
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+ model = AutoModelForCausalLM.from_pretrained("Ahmade/rick-and-morty-v2")
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+
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+ def chat(model, tokenizer):
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+ print("type \"q\" to quit. Automatically quits after 5 messages")
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+
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+ for step in range(5):
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+ message = input("MESSAGE: ")
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+
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+ if message in ["", "q"]: # if the user doesn't wanna talk
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+ break
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+
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+ # encode the new user input, add the eos_token and return a tensor in Pytorch
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+ new_user_input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors='pt')
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+
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+ # append the new user input tokens to the chat history
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+ bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
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+
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+ # generated a response while limiting the total chat history to 1000 tokens,
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+
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+ chat_history_ids = model.generate(
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+ bot_input_ids,
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+ max_length=1000,
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+ pad_token_id=tokenizer.eos_token_id,
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+ no_repeat_ngram_size=3,
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+ do_sample=True,
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+ top_k=100,
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+ top_p=0.7,
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+ temperature = 0.8,
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+ )
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+
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+ # pretty print last ouput tokens from bot
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+ print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
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+
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+ chat(model, tokenizer)