jesseD_-_homer-bot-gguf

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homer-bot - GGUF

• Model creator: https://huggingface.co/jesseD/
• Original model: https://huggingface.co/jesseD/homer-bot/

Original model description:

tags:

• conversational language:
• en

---

HomerBot: A conversational chatbot imitating Homer Simpson

This model is a fine-tuned DialoGPT (medium version) on Simpsons scripts.

More specifically, we fine-tune DialoGPT-medium for 3 epochs on 10K (character utterance, Homer's response) pairs

For more details, check out our git repo containing all the code.

How to use

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch 

tokenizer = AutoTokenizer.from_pretrained("DingleyMaillotUrgell/homer-bot")
model = AutoModelForCausalLM.from_pretrained("DingleyMaillotUrgell/homer-bot")

# Let's chat for 5 lines
for step in range(5):
    # 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')
  
    # 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=1000,                    
        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
    )
    
    # print last outpput tokens from bot
    print("Homer: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))