Instructions to use faisalq/bert-base-arapoembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalq/bert-base-arapoembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faisalq/bert-base-arapoembert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faisalq/bert-base-arapoembert") model = AutoModelForMaskedLM.from_pretrained("faisalq/bert-base-arapoembert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe119ad6a3ff7e87596350acd2de85fa3c21803df08c29318f9024c289495ba3
- Size of remote file:
- 440 MB
- SHA256:
- a3f7947ef14b474e55bbfdf71d2d71580bd6fcc5ed0da34b0eea6f44f4d49bdd
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