Instructions to use chosenone80/arabert-ner-test-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chosenone80/arabert-ner-test-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chosenone80/arabert-ner-test-2")# 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") - Notebooks
- Google Colab
- Kaggle
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
- Downloads last month
- 6
Model tree for chosenone80/arabert-ner-test-2
Base model
aubmindlab/bert-base-arabertv02