Instructions to use Aleph-Alpha/Aleph-Alpha-GermanWeb-Quality-Classifier-fastText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use Aleph-Alpha/Aleph-Alpha-GermanWeb-Quality-Classifier-fastText with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("Aleph-Alpha/Aleph-Alpha-GermanWeb-Quality-Classifier-fastText", "model.bin")) - Notebooks
- Google Colab
- Kaggle
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README.md
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We trained Aleph-Alpha-GermanWeb-Quality-Classifier-fastText using 185,403 documents in each class. We used 95% of the data (and the remaining 5% for validation) to train a fastText model to classify between high and low quality text data. It reached 92% precision and 91.5% recall on the validation set.
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Further details, including our LLM judging prompt, can be found in our
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## Example Snippet
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We trained Aleph-Alpha-GermanWeb-Quality-Classifier-fastText using 185,403 documents in each class. We used 95% of the data (and the remaining 5% for validation) to train a fastText model to classify between high and low quality text data. It reached 92% precision and 91.5% recall on the validation set.
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Further details, including our LLM judging prompt, can be found in our accompanying paper (link to paper coming soon).
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## Example Snippet
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