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--- |
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language: ar |
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widget: |
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- text: " جاب ليا [MASK] ." |
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- text: "مشيت نجيب[MASK] فالفرماسيان ." |
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--- |
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**DarijaBERT** is the first BERT model for the Moroccan Arabic dialect called “Darija”. It is based on the same architecture as BERT-base, but without the Next Sentence Prediction (NSP) objective. This model was trained on a total of ~3 Million sequences of Darija dialect representing 691MB of text or a total of ~100M tokens. |
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The model was trained on a dataset issued from three different sources: |
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* Stories written in Darija scrapped from a dedicated website |
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* Youtube comments from 40 different Moroccan channels |
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* Tweets crawled based on a list of Darija keywords. |
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More details about DarijaBert are available in the dedicated GitHub [repository](https://github.com/AIOXLABS/DBert) |
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**Loading the model** |
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The model can be loaded directly using the Huggingface library: |
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```python |
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from transformers import AutoTokenizer, AutoModel |
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DarijaBERT_tokenizer = AutoTokenizer.from_pretrained("Kamel/DarijaBERT") |
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DarijaBert_model = AutoModel.from_pretrained("Kamel/DarijaBERT") |
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``` |
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**Acknowledgments** |
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We gratefully acknowledge Google’s TensorFlow Research Cloud (TRC) program for providing us with free Cloud TPUs. |
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