An generative AI made using microsoft/DialoGPT-small.

Trained on:

 https://www.kaggle.com/Cornell-University/movie-dialog-corpus

 https://www.kaggle.com/jef1056/discord-data

Important:

  The AI can be a bit weird at times as it is still undergoing training!
  
  At times it send stuff using :<random_wierd_words>: as they are discord emotes.
  
  It also send random @RandomName as it is trying to ping people.
  
  This works well on discord but on the web not so much but it is easy enough to remove such stuff using [re.sub](https://docs.python.org/3/library/re.html#re.sub)

Issues:

 The AI like with all conversation AI lacks a character, it changes its name way too often. This can be solved using an AIML chatbot to give it a stable character!
 

Live Demo

Example:

from transformers import AutoTokenizer, AutoModelWithLMHead
  
tokenizer = AutoTokenizer.from_pretrained("deepparag/DumBot")
model = AutoModelWithLMHead.from_pretrained("deepparag/DumBot")
# Let's chat for 4 lines
for step in range(4):
    # 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=200,
        pad_token_id=tokenizer.eos_token_id,  
        no_repeat_ngram_size=4,       
        do_sample=True, 
        top_k=100, 
        top_p=0.7,
        temperature=0.8
    )
    
    # pretty print last ouput tokens from bot
    print("DumBot: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
Downloads last month
14
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.