Token Classification
Transformers
TensorBoard
Arabic
bert
fill-mask
Named Entity Recognition
Arabic NER
Nested NER
Instructions to use SinaLab/ArabicNER-Wojood with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinaLab/ArabicNER-Wojood with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SinaLab/ArabicNER-Wojood")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SinaLab/ArabicNER-Wojood") model = AutoModelForMaskedLM.from_pretrained("SinaLab/ArabicNER-Wojood", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SinaLab/ArabicNER-Wojood: direct link, hf CLI and curl.
- Browser
- Download file 2.31 MB
-
https://huggingface.co/SinaLab/ArabicNER-Wojood/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://SinaLab/ArabicNER-Wojood@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SinaLab/ArabicNER-Wojood/resolve/refs%2Fpr%2F2/tokenizer.json
2.31 MB
File too large to display, you can check the raw version instead.