Instructions to use faisalq/bert-base-arapoembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalq/bert-base-arapoembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faisalq/bert-base-arapoembert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faisalq/bert-base-arapoembert") model = AutoModelForMaskedLM.from_pretrained("faisalq/bert-base-arapoembert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-nc-4.0
language:
- ar
tags:
- Arabic BERT
- Poetry
- Masked Langauge Model
AraPoemBERT is the first pre-trained large language model focused exclusively on Arabic poetry. The dataset used in pretraining the model contains more than 2 million verses. 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{qarah2024arapoembert,
title={AraPoemBERT: A Pretrained Language Model for Arabic Poetry Analysis},
author={Qarah, Faisal},
journal={arXiv preprint arXiv:2403.12392},
year={2024}
}