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
- Xet hash:
- 5998efc0f3e3c98e262de659ff4f2fa2eca76197c90d51f5750b5df5b0eed414
- Size of remote file:
- 439 MB
- SHA256:
- d234e4fe0193e74036b1db72ba9b41a2e4921d8cf0c3c421d1f6a6d8816af729
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