meitei-roberta

from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline

# Using the lowercase repository ID for robust loading
REPO_ID = "MWirelabs/meitei-roberta" 

# 1. Load Model and Tokenizer
tokenizer = AutoTokenizer.from_pretrained(REPO_ID)
model = AutoModelForMaskedLM.from_pretrained(REPO_ID)

# 2. Example: Tokenize Text
# NOTE: Example text MUST be in the Bengali script, as the model was trained only on this script.
meitei_text = "আমি গতকাল স্কুল থেকে ফিরেছি। এই বইটি পড়তে ভাল লাগে।" 
inputs = tokenizer(meitei_text, return_tensors="pt")

# 3. Example: Fill-Mask Pipeline Test (Testing fluency)
unmasker = pipeline("fill-mask", model=model, tokenizer=tokenizer)
# Masking a word in Bengali script Meitei
results = unmasker("আমাদের দেশে <mask> অনেক সমস্যা আছে।") 
# ... process results

@inproceedings{nyalang-2026-beyond,
  title     = {Beyond Multilinguality: Typological Limitations in Multilingual Models for Meitei Language},
  author    = {Nyalang, Badal},
  booktitle = {Proceedings of the 8th Workshop on Research in Computational Linguistic Typology and Multilingual NLP},
  pages     = {32--38},
  year      = {2026},
  publisher = {Association for Computational Linguistics},
  url       = {https://aclanthology.org/2026.sigtyp-main.5}
}