Fill-Mask
Transformers
Safetensors
Arabic
bert
Arabic BERT
Saudi Dialect
Twitter
Masked Langauge Model
Instructions to use faisalq/SaudiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalq/SaudiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faisalq/SaudiBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faisalq/SaudiBERT") model = AutoModelForMaskedLM.from_pretrained("faisalq/SaudiBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-nc-4.0
language:
- ar
tags:
- Arabic BERT
- Saudi Dialect
- Twitter
- Masked Langauge Model
widget:
- text: اللي ما يعرف الصقر [MASK].
SaudiBERT is the first pre-trained large language model focused exclusively on Saudi dialect text. The model was pretrained on two large-scale corpora: the Saudi Tweets Mega Corpus (STMC), which contains +141 million tweets, and the Saudi Forum Corpus, which includes +70 million sentences collected from various Saudi online forums. The datasets comprise 26.3GB of text. The code files along with the results are available on repo.
BibTex
If you use SaudiBERT model in your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (citation details to be updated):
@article{qarah2024saudibert,
title={SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora},
author={Qarah, Faisal},
journal={arXiv preprint arXiv:2405.06239},
year={2024}
}