krinal/BertWordPieceTokenizer-hi

Model Details

BertWordPieceTokenizer

• tokenizer for hindi language

Usage

from transformers import AutoTokenizer

hi_tokenizer = AutoTokenizer.from_pretrained('krinal/BertWordPieceTokenizer-hi')

hi_str = "आज का सूर्य देखो, कितना प्यारा, कितना शीतल है"

# encode text
encoded_str = hi_tokenizer.encode(hi_str)

# decode text
decoded_str = hi_tokenizer.decode(encoded_str)

Language

• hi

Training

• For training see Train BertWordPieceTokenizer

Dataset

• trained on BHAAV (hi sentiment analysis dataset)
• dataset source: Bhaav
• Hindi text corpus (20,304 sentences)

Citation

@article{kumar2019bhaav,
  title={BHAAV-A Text Corpus for Emotion Analysis from Hindi Stories},
  author={Kumar, Yaman and Mahata, Debanjan and Aggarwal, Sagar and Chugh, Anmol and Maheshwari, Rajat and Shah, Rajiv Ratn},
  journal={arXiv preprint arXiv:1910.04073},
  year={2019}
}