Low-Resource Languages
Collection
Towards more transparent, inclusive, and culture-aware NLP for low-resource languages!
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5 items
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Updated
We continually pretrain llama_chinese_13b with MC^2, which supports Tibetan, Uyghur, Kazakh in the Kazakh Arabic script, and Mongolian in the traditional Mongolian script.
See details in the paper.
We have also released another model trained on MC^2: MC^2XLMR-large.
the model and tokenizer can be loaded via:
from transformers import LlamaForCausalLM, LlamaTokenizer
tokenizer = LlamaTokenizer.from_pretrained("pkupie/mc2-llama-13b")
model = LlamaForCausalLM.from_pretrained("pkupie/mc2-llama-13b")
@article{zhang2024mc,
title={MC$^2$: Towards Transparent and Culturally-Aware NLP for Minority Languages in China},
author={Zhang, Chen and Tao, Mingxu and Huang, Quzhe and Lin, Jiuheng and Chen, Zhibin and Feng, Yansong},
journal={arXiv preprint arXiv:2311.08348},
year={2024}
}