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--- |
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language: |
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- en |
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thumbnail: |
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tags: |
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- gpt2 |
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- conversational |
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license: apache-2.0 |
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datasets: |
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- wikipedia-turkish |
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metrics: |
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- perplexity |
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- accuracy |
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widget: |
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- text: Bu yazıyı bir bilgisayar yazdı. Yazarken |
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context: '' |
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- text: İnternete kolay erişim sayesinde dünya daha da küçüldü. Bunun sonucunda |
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context: '' |
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--- |
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# GPT2 Persona Chatbot based on Movie Characters |
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Model used for https://www.metayazar.com/chatbot |
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GPT2 Small Trained on movie scripts (especially Sci-fi) |
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This work is based on Persona Chatbot originally done by Hugging Face team (https://medium.com/huggingface/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-learning-2d818ac26313) |
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For cleaning movie scripts I also provide cleaner code |
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https://github.com/gorkemgoknar/moviescriptcleaner |
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Example persona how to: |
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https://gist.github.com/gorkemgoknar/ae29bf9d14fa814e6a64d0e57a4a4ed7 |
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For obvious reasons I cannot share raw personafile but you can check above gist for example how to create it. |
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A working "full" demo can be seen in https://www.metayazar.com/chatbot |
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For Turkish version (with limited training) https://www.metayazar.com/chatbot_tr |
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```python |
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tokenizer = AutoTokenizer.from_pretrained('microsoft/DialoGPT-small') |
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model = AutoModelWithLMHead.from_pretrained('output-small') |
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# Let's chat for 5 lines |
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for step in range(100): |
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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=500, |
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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("AI: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True))) |
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``` |
