Youth_ Chatbot_ Kogpt2 base

Introduction

The Youth_Chatbot_KoGPT2-base model is a Korean language model based on KoGPT2, designed for text generation tasks. It is developed by EasthShin and leverages the Aihub dataset for training.

Architecture

The model is built on the GPT-2 architecture and utilizes the Transformers library for implementation. It uses PyTorch as its backend framework, facilitating integration with various machine learning workflows.

Training

The Youth_Chatbot_KoGPT2-base model was trained on the Aihub dataset, which provides a comprehensive collection of Korean text to enhance the model's language understanding and generation capabilities. This setup allows the model to effectively handle Korean language text generation tasks.

Guide: Running Locally

To run the Youth_Chatbot_KoGPT2-base model locally, follow these basic steps:

1. Install the Transformers library: Ensure that you have the transformers library installed in your environment.

   pip install transformers
   

2. Load the Tokenizer and Model: Use the following code to load the necessary tokenizer and model.

   from transformers import PreTrainedTokenizerFast, GPT2LMHeadModel
   tokenizer = PreTrainedTokenizerFast.from_pretrained("EasthShin/Youth_Chatbot_Kogpt2-base",
     bos_token='</s>', eos_token='</s>', unk_token='<unk>',
     pad_token='<pad>', mask_token='<unused0>')
   
   model = GPT2LMHeadModel.from_pretrained('EasthShin/Youth_Chatbot_Kogpt2-base')
   

3. Generate Text: Encode your input text and generate a response using the loaded model.

   input_ids = tokenizer.encode('<usr>' + {your text} + '<unused1>' + '<sys>')
   gen_ids = model.generate(torch.tensor([input_ids]),
                                    max_length=128,
                                    repetition_penalty=2.0,
                                    pad_token_id=tokenizer.pad_token_id,
                                    eos_token_id=tokenizer.eos_token_id,
                                    bos_token_id=tokenizer.bos_token_id,
                                    use_cache=True)
   
   generated = tokenizer.decode(gen_ids[0, :].tolist())
   print(generated)
   

4. Suggest Cloud GPUs: For enhanced performance, consider using cloud GPU resources available from providers such as AWS, Google Cloud, or Azure.

License

Details about the license for Youth_Chatbot_KoGPT2-base are not specified in the provided content. Please check the original repository or contact the author for licensing information.