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
- Xet hash:
- 9352bed368cd52442f72f0e0954161ca152acedd514fbaf8daa46443cff92fd2
- Size of remote file:
- 709 MB
- SHA256:
- 654c7b7053014cddf568b52580cdab0230d79f7222be9ef4c758b1ce7c6635a0
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