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
Commit History
-
Upload 11 files
Verified signature1cee3d6
-
Wo
609bfce
-
Update Nested NER model
a585746
-
Delete checkpoints/checkpoint_7.pt
cfdb0df -
Delete checkpoints/checkpoint_6.pt
bd39ee2 -
Delete checkpoints/checkpoint_5.pt
f2920c0 -
Delete checkpoints/checkpoint_4.pt
896dec5 -
Delete checkpoints/checkpoint_3.pt
1d52aa8 -
Delete checkpoints/checkpoint_2.pt
8b04740 -
Delete checkpoints/checkpoint_1.pt
ff62f4f -
Delete checkpoints/checkpoint_0.pt
33f05c1 -
initial commit
75ba8dc