Dialogpt Medium

🚀 A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)

DialoGPT is a state-of-the-art large-scale pretrained dialogue response generation model designed for multiturn conversations. It offers high-quality responses, as shown by human evaluation results, which suggest that its single-turn responses can rival those of humans in a Turing test. The model is trained on 147M multi-turn dialogues sourced from Reddit discussion threads.

✨ Features

• Multi-turn Dialogue: Capable of engaging in multi-turn conversations, providing coherent and context-aware responses.
• High-quality Responses: The generated responses are comparable to human responses in quality, as demonstrated by human evaluation.

📦 Installation

The installation steps are not explicitly provided in the original README. However, the usage example implies that you need to have the transformers library installed. You can install it using the following command:

pip install transformers torch

💻 Usage Examples

Basic Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch


tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")

# 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)

    # pretty print last ouput tokens from bot
    print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))

Example of Multi-turn Generation

📚 Documentation

Please find the information about preprocessing, training, and full details of the DialoGPT in the original DialoGPT repository.

ArXiv paper: https://arxiv.org/abs/1911.00536

📄 License

This project is licensed under the MIT license.