Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
Arabic
bert
Arabic
Dialect
Egyptian
Gulf
Levantine
Classical Arabic
MSA
Modern Standard Arabic
Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-mix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/bert-base-arabic-camelbert-mix with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAMeL-Lab/bert-base-arabic-camelbert-mix")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix") - Inference
- Notebooks
- Google Colab
- Kaggle
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- [Arabic Wikipedia](https://archive.org/details/arwiki-20190201)
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- The unshuffled version of the Arabic [OSCAR corpus](https://oscar-corpus.com/)
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- DA
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- A collection of dialectal Arabic data described in our paper.
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- CA
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- [OpenITI (Version 2020.1.2)](https://zenodo.org/record/3891466#.YEX4-F0zbzc)
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- [Arabic Wikipedia](https://archive.org/details/arwiki-20190201)
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- The unshuffled version of the Arabic [OSCAR corpus](https://oscar-corpus.com/)
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- DA
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- A collection of dialectal Arabic data described in [our paper](https://arxiv.org/abs/2103.06678).
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- CA
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- [OpenITI (Version 2020.1.2)](https://zenodo.org/record/3891466#.YEX4-F0zbzc)
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