Text Classification
Transformers
PyTorch
Safetensors
German
bert
easy-language
plain-language
leichte-sprache
einfache-sprache
text-complexity
text-embeddings-inference
Instructions to use krupper/text-complexity-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krupper/text-complexity-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="krupper/text-complexity-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("krupper/text-complexity-classification") model = AutoModelForSequenceClassification.from_pretrained("krupper/text-complexity-classification") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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>>> classifier("Bei Kleinkindern unter 2 Jahren liegen nur begrenzte Erfahrungen zur Pharmakokinetik vor.")
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[{'label': 'special_language', 'score': 0.999923825263977}]
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```
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>>> classifier("Bei Kleinkindern unter 2 Jahren liegen nur begrenzte Erfahrungen zur Pharmakokinetik vor.")
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[{'label': 'special_language', 'score': 0.999923825263977}]
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```
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DOI: [https://doi.org/10.57967/hf/0131](https://doi.org/10.57967/hf/0131)
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