---
language:
- en
thumbnail:
tags:
- gpt2
- conversational
license: apache-2.0
datasets:
- wikipedia-turkish
metrics:
- perplexity
- accuracy
widget:
- text: Bu yazıyı bir bilgisayar yazdı. Yazarken
  context: ''
- text: İnternete kolay erişim sayesinde dünya daha da küçüldü. Bunun sonucunda
  context: ''
---
# GPT2 Persona Chatbot based on Movie Characters
Model used for https://www.metayazar.com/chatbot
GPT2 Small Trained on movie scripts (especially Sci-fi) 
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)
For cleaning movie scripts I also provide cleaner code
https://github.com/gorkemgoknar/moviescriptcleaner

Example persona how to:
https://gist.github.com/gorkemgoknar/ae29bf9d14fa814e6a64d0e57a4a4ed7

For obvious reasons I cannot share raw personafile but you can check above gist for example how to create it.

A working "full" demo can be seen in https://www.metayazar.com/chatbot
For Turkish version (with limited training) https://www.metayazar.com/chatbot_tr


```python
tokenizer = AutoTokenizer.from_pretrained('microsoft/DialoGPT-small')
model = AutoModelWithLMHead.from_pretrained('output-small')
# Let's chat for 5 lines
for step in range(100):
    # encode the new user input, add the eos_token and return a tensor in Pytorch
    new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
    # print(new_user_input_ids)
    # append the new user input tokens to the chat history
    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
    # generated a response while limiting the total chat history to 1000 tokens, 
    chat_history_ids = model.generate(
        bot_input_ids, max_length=500,
        pad_token_id=tokenizer.eos_token_id,  
        no_repeat_ngram_size=3,       
        do_sample=True, 
        top_k=100, 
        top_p=0.7,
        temperature = 0.8
    )
    
    # pretty print last ouput tokens from bot
    print("AI: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
```