# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("chosenone80/arabert-ner-test-2")
model = AutoModelForTokenClassification.from_pretrained("chosenone80/arabert-ner-test-2", device_map="auto")Quick Links
arabert-ner-test-2
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
aubmindlab/bert-base-arabertv02
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chosenone80/arabert-ner-test-2")