Instructions to use GKLMIP/roberta-tagalog-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GKLMIP/roberta-tagalog-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GKLMIP/roberta-tagalog-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GKLMIP/roberta-tagalog-base") model = AutoModelForMaskedLM.from_pretrained("GKLMIP/roberta-tagalog-base") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
https://github.com/GKLMIP/Pretrained-Models-For-Tagalog
If you use our model, please consider citing our paper:
@InProceedings{,
author="Jiang, Shengyi
and Fu, Yingwen
and Lin, Xiaotian
and Lin, Nankai",
title="Pre-trained Language models for Tagalog with Multi-source data",
booktitle="Natural Language Processing and Chinese Computing",
year="2021",
publisher="Springer International Publishing",
address="Cham",
}
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