Instructions to use Enigma-for-AI/bert-base-sudabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Enigma-for-AI/bert-base-sudabert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Enigma-for-AI/bert-base-sudabert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Enigma-for-AI/bert-base-sudabert") model = AutoModel.from_pretrained("Enigma-for-AI/bert-base-sudabert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Verified signature# SudaBERT Model A pretrained BERT base language model for Sudanese Arabic. ## Usage ```python from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Enigma-for-AI/bert-base-sudabert") model = AutoModelForMaskedLM.from_pretrained("Enigma-for-AI/bert-base-sudabert") ``` ## Citation _If you use this model in your work, please cite this paper:_ ``` @INPROCEEDINGS{SudaBERT, author={Elgezouli, Mukhtar and Elmadani, Khalid N. and Saeed, Muhammed}, booktitle={2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)}, title={SudaBERT: A Pre-trained Encoder Representation For Sudanese Arabic Dialect}, year={2021}, pages={1-4}, doi={10.1109/ICCCEEE49695.2021.9429651}} ```6f96d8e
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