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--- |
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language: |
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- ar |
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- dz |
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tags: |
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- pytorch |
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- bert |
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- multilingual |
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- ar |
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- dz |
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widget: |
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- text: "Baraka ellaho fik khouya la3ziz rabi yahfdek" |
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- text: "123 viva l'Agérie, tahya el djazair !" |
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- text: "ye3ayi l film hedak ghir akhtik" |
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- text: "Dzayer mech ghir el3assima sadi9i" |
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- text: "سخانة بزاف ليوم.. الجمل يرعف" |
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inference: true |
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--- |
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<img src="https://raw.githubusercontent.com/alger-ia/dziribert/main/dziribert_drawing.png" alt="drawing" width="25%" height="25%" align="right"/> |
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# DziriBERT Sentiment |
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DziriBERT is the first Transformer-based Language Model that has been pre-trained specifically for the Algerian Dialect. It handles Algerian text contents written using both Arabic and Latin characters. |
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This is a fine-tuned version that is ready to use for sentiment classification. |
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For more information, please visit our paper: https://arxiv.org/pdf/2109.12346.pdf. |
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## How to use |
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```python |
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from transformers import BertTokenizer, BertForSequenceClassification |
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tokenizer = BertTokenizer.from_pretrained("alger-ia/dziribert_sentiment") |
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model = BertForSequenceClassification.from_pretrained("alger-ia/dziribert_sentiment") |
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``` |
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You can find a fine-tuning script in our Github repo: https://github.com/alger-ia/dziribert |
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### How to cite |
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```bibtex |
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@article{dziribert, |
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title={DziriBERT: a Pre-trained Language Model for the Algerian Dialect}, |
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author={Abdaoui, Amine and Berrimi, Mohamed and Oussalah, Mourad and Moussaoui, Abdelouahab}, |
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journal={arXiv preprint arXiv:2109.12346}, |
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year={2021} |
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} |
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``` |
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## Contact |
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Please contact amine.abdaoui.nlp@gmail.com for any question, feedback or request. |
