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:
- 1da826a91d24cdf01e277b56f49731728b20827950cd0916c25739655afe964a
- Size of remote file:
- 3.96 kB
- SHA256:
- 51f6cfaebe32e520e92a073b657df5109a530df91f9659061cc0ba324a91b7b2
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