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")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("PRAli22/arabert_arabic_ner") model = AutoModelForTokenClassification.from_pretrained("PRAli22/arabert_arabic_ner") - Notebooks
- Google Colab
- Kaggle
AraBERT_Arabic_NER
This is fine tuned AraBERT model for Arabic NER
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation results
Accuracy score was about 97% F1 score was 0.82
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
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