Text Classification
Transformers
Safetensors
deberta
human value detection
text classification
multi-label clasification
Instructions to use VictorYeste/deberta-based-human-value-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VictorYeste/deberta-based-human-value-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VictorYeste/deberta-based-human-value-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VictorYeste/deberta-based-human-value-detection") model = AutoModelForSequenceClassification.from_pretrained("VictorYeste/deberta-based-human-value-detection") - Notebooks
- Google Colab
- Kaggle
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README.md
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```
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@inproceedings{yeste2024philo,
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title={Philo of Alexandria at touch{\'e}: a cascade model approach to human value detection},
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author={Yeste, V{\'\i}ctor and Ardanuy,
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booktitle={Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024). CEUR Workshop Proceedings, CEUR-WS. org},
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year={2024}
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}
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```
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@inproceedings{yeste2024philo,
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title={Philo of Alexandria at touch{\'e}: a cascade model approach to human value detection},
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author={Yeste, V{\'\i}ctor and Coll-Ardanuy, M and Rosso, Paolo},
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booktitle={Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024). CEUR Workshop Proceedings, CEUR-WS. org},
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year={2024}
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}
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