49 lines
1.7 KiB
Markdown
49 lines
1.7 KiB
Markdown
---
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tags:
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- conversational
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language:
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- en
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---
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# HomerBot: A conversational chatbot imitating Homer Simpson
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This model is a fine-tuned [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium) (medium version) on Simpsons [scripts](https://www.kaggle.com/datasets/pierremegret/dialogue-lines-of-the-simpsons).
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More specifically, we fine-tune DialoGPT-medium for 3 epochs on 10K **(character utterance, Homer's response)** pairs
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For more details, check out our git [repo](https://github.com/jesseDingley/HomerBot) containing all the code.
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### How to use
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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tokenizer = AutoTokenizer.from_pretrained("DingleyMaillotUrgell/homer-bot")
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model = AutoModelForCausalLM.from_pretrained("DingleyMaillotUrgell/homer-bot")
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# Let's chat for 5 lines
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for step in range(5):
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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(input(">> User: ") + tokenizer.eos_token, return_tensors='pt')
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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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# generated a response while limiting the total chat history to 1000 tokens,
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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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# print last outpput tokens from bot
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print("Homer: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
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```
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