roberta small japanese aozora char

Introduction

The RoBERTa-Small-Japanese-Aozora-Char model is a RoBERTa-based model pre-trained on Japanese texts from 青空文庫 (Aozora Bunko) using a character tokenizer. It is designed for tasks such as POS-tagging and dependency parsing.

Architecture

This model employs the RoBERTa architecture, which is a robustly optimized BERT approach. It utilizes a character-level tokenizer to process Japanese text, making it suitable for fine-tuning on various natural language processing tasks.

Training

The model is pre-trained on texts from the Aozora Bunko library. It is specifically optimized for the Japanese language and can be adapted to perform various tasks, including masked language modeling, POS-tagging, and dependency parsing.

Guide: Running Locally

To run the model locally, follow these basic steps:

1. Install Transformers Library:
   Ensure you have the transformers library installed. You can install it using pip:

   pip install transformers
   

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

   from transformers import AutoTokenizer, AutoModelForMaskedLM
   
   tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-small-japanese-aozora-char")
   model = AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-small-japanese-aozora-char")
   

3. Select Hardware:
   For improved performance, consider using a cloud GPU service such as AWS, Azure, or Google Cloud Platform.

License

This model is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).