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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac9d962dfe3f991a44f45458183eb758c2241f1c378040ce2d01e7275c1ade95
- Size of remote file:
- 437 MB
- SHA256:
- 0e5b788e88bb1646ae054c868067e52b301331fbab6f8a6deff7119bf76a9224
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