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:
- 73663ebbdc2ad9d7564a0995c28d25d78af54dff0024eb45008debf21d9ba9fb
- Size of remote file:
- 1.98 kB
- SHA256:
- c6abda986c66dd2dd56420aa4edd75177b885830bebd40152fb2951f87d663ed
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