Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-ca-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-ca-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-ca-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-ca-pos-glf") model = AutoModelForTokenClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf: direct link, hf CLI and curl.
- Browser
- Download file 868 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf/resolve/main/optimizer.pt
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf/resolve/main/optimizer.pt
868 MB
- Xet hash:
- 3c53ef232162d321885aa75fbc9dd7fbde5482de06ea95b2ee0060a9b920d374
- Size of remote file:
- 868 MB
- SHA256:
- ac0a1735fb7bdc536c74ff783c9fbe64905cc0b8d3cfc76dd0ec3ca6e5fcec7a
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