Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth 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-eighth 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-eighth")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31f79e8c0a4286ec325abcccebaf97a24e0695d910496a43032461ccd2d2b758
- Size of remote file:
- 439 MB
- SHA256:
- 841750c8dbb698276dfbb32f938c1cc4ec645a0c22d7912e6909e361a6e3ac97
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