Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf 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-mix-pos-glf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf") model = AutoModelForTokenClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 83576eb1618d70e4695ce34d06b0647bfcb81779e3153efdae15fdef3323f554
- Size of remote file:
- 436 MB
- SHA256:
- f0b4af01e1102d1432f4352bd483da7d1718d7a6aaa3d1a64f0dbedf705418be
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