Instructions to use Marmara-NLP/Turna_Question_answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Marmara-NLP/Turna_Question_answering with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("Marmara-NLP/Turna_Question_answering", set_active=True) - Notebooks
- Google Colab
- Kaggle
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README.md
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This model can be used as a starting point to further train the Turna model for question answering, for now it's still not well trained and may require a larger dataset
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## Training and evaluation data
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- This is a multilingual corpus of Frequently Asked Questions parsed from the Common Crawl.
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## Training procedure
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This model can be used as a starting point to further train the Turna model for question answering, for now it's still not well trained and may require a larger dataset
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## Training and evaluation data
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Clips/Mfaq turkish dataset: huggingface.co/datasets/clips/mfaq/viewer/tr_flat
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Size: 100k rows training, 2.7k validation
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This is a multilingual corpus of Frequently Asked Questions parsed from the Common Crawl.
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## Training procedure
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