Instructions to use HikmaLabs/ukhbert_narrator_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HikmaLabs/ukhbert_narrator_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HikmaLabs/ukhbert_narrator_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HikmaLabs/ukhbert_narrator_detection") model = AutoModelForTokenClassification.from_pretrained("HikmaLabs/ukhbert_narrator_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 182 Bytes
1b12e93 | 1 2 3 4 5 6 7 | acc = 0.9886209625807463 correct_hadith = 0.7687676387582314 eval_loss = 0.05440825115018377 f1_score = 0.9607255174431361 precision = 0.9398847389714969 recall = 0.9825114912829439 |