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
add linking model to get narrator ids
Browse files
README.md
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'end': 144}]
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```
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# Training
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Ukhbert is finetuned from the ARABERT v0.1 model. For more details,
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please consult the referenced paper, "Learning to identify Narrators in Classical Islamic Texts"
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'end': 144}]
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```
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To identify the narrators (ie get biographical info of the narrator), it is highly recommended to use the Narrator linking
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Model [HikmaLabs/ukhbert_narrator_linking](https://huggingface.co/HikmaLabs/ukhbert_narrator_linking)
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# Training
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Ukhbert is finetuned from the ARABERT v0.1 model. For more details,
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please consult the referenced paper, "Learning to identify Narrators in Classical Islamic Texts"
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