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---
language: ar
datasets:
- wikipedia
- OSIAN
- 1.5B Arabic Corpus
- OSCAR Arabic Unshuffled
widget:
- text: " جاب ليا [MASK] ."
---
**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.
The model was trained on a dataset issued from three different sources:
* Stories written in Darija scrapped from a dedicated website
* Youtube comments from 40 different Moroccan channels
* Tweets crawled based on a list of Darija keywords.
More details about DarijaBert are available in the dedicated GitHub [repository](https://github.com/AIOXLABS/DBert)
**Loading the model**
The model can be loaded directly using the Huggingface library:
```python
from transformers import AutoTokenizer, AutoModel
DBERT_tokenizer = AutoTokenizer.from_pretrained("Kamel/DarijaBERT")
DBERT_Bert_model = AutoModel.from_pretrained("Kamel/DarijaBERT")
```
**Acknowledgments**
We gratefully acknowledge Google’s TensorFlow Research Cloud (TRC) program for providing us with free Cloud TPUs.
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