Instructions to use universalner/uner_qaf_ara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_qaf_ara with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_qaf_ara")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_qaf_ara") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_qaf_ara") - Notebooks
- Google Colab
- Kaggle
| { | |
| "predict_accuracy": 0.9545663148233134, | |
| "predict_f1": 0.7088607594936709, | |
| "predict_loss": 0.1624361276626587, | |
| "predict_precision": 0.6965174129353234, | |
| "predict_recall": 0.7216494845360825, | |
| "predict_runtime": 0.4848, | |
| "predict_samples_per_second": 301.185, | |
| "predict_steps_per_second": 20.629 | |
| } |