Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-msa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/bert-base-arabic-camelbert-msa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAMeL-Lab/bert-base-arabic-camelbert-msa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0a014ef3fe0b6f5519afde6ad8391a9e910a82e0360e71491fdd8e685491f59
- Size of remote file:
- 436 MB
- SHA256:
- 0fea0503cc43d28f0bb8a448440db8681327f653b36f619382fe4a8726686dc3
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