roberta large

Introduction

KLUE RoBERTa Large is a pretrained model designed for the Korean language, part of the KLUE (Korean Language Understanding Evaluation) benchmark. It is based on the RoBERTa architecture and is tailored for tasks that involve Korean text.

Architecture

The model uses the RoBERTa architecture, which is a robustly optimized BERT variant. It is specifically trained on a large corpus of Korean text to enhance understanding and performance on Korean language tasks.

Training

KLUE RoBERTa Large is pretrained on a diverse set of Korean texts. The model is designed to handle fill-mask tasks using [MASK] tokenization. The model should be used with BertTokenizer for tokenization processes, despite being a RoBERTa model.

Guide: Running Locally

1. Installation: Ensure you have the transformers library installed.

   pip install transformers
   

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

   from transformers import AutoModel, AutoTokenizer
   
   model = AutoModel.from_pretrained("klue/roberta-large")
   tokenizer = AutoTokenizer.from_pretrained("klue/roberta-large")
   

3. Environment: Running the model may require substantial computational resources. It is recommended to use a cloud GPU service such as AWS, Google Cloud, or Azure for efficient processing.

License

For licensing details, refer to the KLUE benchmark repository and the associated documentation.