Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-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-mix-pos-msa 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-msa")# 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-msa") model = AutoModelForTokenClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa: direct link, hf CLI and curl.
- Browser
- Download file 868 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa/resolve/main/optimizer.pt
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa/resolve/main/optimizer.pt
868 MB
- Xet hash:
- e5bac79e5c6220b4965f6b11f1712b70e5e3afd0ef15e23d8258b8a05bc4a8c6
- Size of remote file:
- 868 MB
- SHA256:
- b82d8193ad604a8fd8b188a0b900525971dd9183c34e03067451d190a6ee19c2
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