Mizbert

🚀 MizBERT: A Masked Language Model for Mizo Text Understanding

MizBERT is a pre - trained masked language model designed for Mizo text understanding. It is based on the BERT architecture and uses the MLM objective to learn word representations in the Mizo language, offering great potential for various Mizo NLP tasks.

🚀 Quick Start

To use MizBERT in your Mizo NLP projects, you can install it from the Hugging Face Transformers library:

pip install transformers

Then, import and use MizBERT like other pre - trained models in the library:

from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("robzchhangte/mizbert")
model = AutoModelForMaskedLM.from_pretrained("robzchhangte/mizbert")

💻 Usage Examples

Basic Usage

from transformers import pipeline

fill_mask = pipeline("fill-mask", model="robzchhangte/mizbert")

sentence = "Miten kan thiltih [MASK] min teh thin" ##Expected token "atangin". In English: A tree is known by its fruit.
predictions = fill_mask(sentence)

for prediction in predictions:
    print(prediction["sequence"].replace("[CLS]", "").replace("[SEP]", "").strip(), "| Score:", prediction["score"])

✨ Features

• Mizo - Specific: MizBERT is specifically tailored to the Mizo language, capturing its unique linguistic nuances and vocabulary.
• MLM Objective: The MLM objective trains MizBERT to predict masked words based on the surrounding context, fostering a deep understanding of Mizo semantics.
• Contextual Embeddings: MizBERT generates contextualized word embeddings that encode the meaning of a word in relation to its surrounding text.
• Transfer Learning: MizBERT's pre - trained weights can be fine - tuned for various downstream tasks in Mizo NLP, such as text classification, question answering, and sentiment analysis.

📚 Documentation

Potential Applications

• Mizo NLP Research: MizBERT can serve as a valuable foundation for further research in Mizo natural language processing.
• Mizo Machine Translation: Fine - tuned MizBERT models can be used to develop robust machine translation systems for Mizo and other languages.
• Mizo Text Classification: MizBERT can be adapted for tasks like sentiment analysis, topic modeling, and spam detection in Mizo text.
• Mizo Question Answering: Fine - tuned MizBERT models can power question answering systems that can effectively answer questions posed in Mizo.
• Mizo Chatbots: MizBERT can be integrated into chatbots to enable them to communicate and understand Mizo more effectively.

📄 License

This project is licensed under the Apache - 2.0 license.

📚 Citation

If you used this model please cite us as:

@article{lalramhluna2024mizbert,
  title={MizBERT: A Mizo BERT Model},
  author={Lalramhluna, Robert and Dash, Sandeep and Pakray, Dr Partha},
  journal={ACM Transactions on Asian and Low - Resource Language Information Processing},
  year={2024},
  publisher={ACM New York, NY}
}

Demo Application: [https://huggingface.co/spaces/robzchhangte/Mizo - MLM](https://huggingface.co/spaces/robzchhangte/Mizo - MLM)