kobert

Introduction
KoBERT is a Korean language model based on the BERT architecture, designed to perform tasks like feature extraction. It utilizes libraries such as PyTorch and JAX, and supports the use of safetensors for secure data handling.

Architecture
KoBERT employs the BERT architecture tailored for the Korean language. It leverages transformers, making it suitable for a wide range of natural language processing tasks, particularly those requiring deep contextual understanding.

Training
The model was trained with a focus on Korean text, enabling it to understand and process linguistic nuances specific to the language. For more detailed training information, users can refer to the original GitHub repository linked in the reference section.

Guide: Running Locally
To run KoBERT locally, follow these steps:

1. Install Dependencies: Ensure you have Python and the Transformers library installed.
2. Import the Model and Tokenizer:

   from transformers import AutoModel, AutoTokenizer
   
   model = AutoModel.from_pretrained("monologg/kobert")
   tokenizer = AutoTokenizer.from_pretrained("monologg/kobert", trust_remote_code=True)
   

3. Usage: Use the model for feature extraction or other NLP tasks as needed.

For enhanced performance, consider using cloud GPUs from providers such as AWS, Google Cloud, or Azure.

License
KoBERT is licensed under the Apache 2.0 License, which permits free use, modification, and distribution of the software.