Instructions to use PRAli22/arabert_arabic_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PRAli22/arabert_arabic_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="PRAli22/arabert_arabic_ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("PRAli22/arabert_arabic_ner") model = AutoModelForTokenClassification.from_pretrained("PRAli22/arabert_arabic_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature56e3c5b -
Update README.md
Verified signatured55d03d -
Update README.mdโ
Verified signaturethis is fine tuned AraBERT model it was trained on Arabic NER dataset to recognize the entities within the Arabian sentencesd44ca9f -
Create README.md
Verified signature1b62cf7 -
Adding `safetensors` variant of this model (#1)โ
Verified signature- Adding `safetensors` variant of this model (811bb83f79c56128254c50eaec2b57c668aafbe6) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>3d2a1c9
-
Upload BertForTokenClassification
33dd566 -
Upload tokenizer
3a4d026 -
initial commit
b0379ce