Instructions to use SI2M-Lab/DarijaBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SI2M-Lab/DarijaBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SI2M-Lab/DarijaBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SI2M-Lab/DarijaBERT") model = AutoModelForMaskedLM.from_pretrained("SI2M-Lab/DarijaBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Add Moroccan Arabic (Darija) tag to metadata.
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by ayymen - opened
README.md
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language:
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- text: " جاب ليا [MASK] ."
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- text: "مشيت نجيب[MASK] فالفرماسيان ."
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language:
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- ar
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- ary
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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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