Instructions to use asafaya/bert-base-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/bert-base-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/bert-base-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-base-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/bert-base-arabic", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e9608564b46ba7125a9ebe3e4df28b4875e3e12667464324d5a86c84836425e
- Size of remote file:
- 445 MB
- SHA256:
- 6f75e192812243562c99360711ceda556c401bc01c6b34e356885e010481be33
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