Instructions to use asafaya/bert-large-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/bert-large-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/bert-large-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-large-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/bert-large-arabic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a00923530d468a79778425a52195ed2cfc262a1dc2c4751ee6d59df2ad9bf914
- Size of remote file:
- 1.35 GB
- SHA256:
- 4e885bed9fb3ecdb5a3b9ee59707b12513f4fde723d65221a500b67ec7358206
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