49 lines
1.7 KiB
Markdown
49 lines
1.7 KiB
Markdown
---
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thumbnail: https://i.imgur.com/7HAcbbD.gif
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tags:
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- conversational
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license: mit
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---
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# DialoGPT Trained on the Speech of a TV Series Character
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This is an instance of [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) trained on a TV series character, Sheldon from [The Big Bang Theory](https://en.wikipedia.org/wiki/The_Big_Bang_Theory). The data comes from [a Kaggle TV series script dataset](https://www.kaggle.com/mitramir5/the-big-bang-theory-series-transcript).
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Chat with the model:
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```python
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from transformers import AutoTokenizer, AutoModelWithLMHead
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tokenizer = AutoTokenizer.from_pretrained("spirax/DialoGPT-medium-sheldon")
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model = AutoModelWithLMHead.from_pretrained("spirax/DialoGPT-medium-sheldon")
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# Let's chat for 4 lines
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for step in range(4):
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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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# print(new_user_input_ids)
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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, max_length=200,
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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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# pretty print last ouput tokens from bot
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print("SheldorBot: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
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``` |