Instructions to use faisalq/bert-base-arabic-bbpe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalq/bert-base-arabic-bbpe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="faisalq/bert-base-arabic-bbpe")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("faisalq/bert-base-arabic-bbpe") model = AutoModel.from_pretrained("faisalq/bert-base-arabic-bbpe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10a139f32e4341b50a8217b8aa750486591e1b6d9b5d72aa9eee7392563132cb
- Size of remote file:
- 497 MB
- SHA256:
- 7efdd1875846b6cb8b9c7f57ddc7a9c1bfa29ce97c448aca529c09bd712bdf72
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