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pipeline_tag: text-classification
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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<!-- - **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed] -->
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- **License:** MIT
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- **Finetuned from model:** `microsoft/deberta-v3-large`
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- **Repository:** https://github.com/angelosps/DELTA
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- **Paper:** [Transformers in the Service of Description Logic-based Contexts](https://arxiv.org/abs/2311.08941)
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<!-- - **Demo [optional]:** [More Information Needed] -->
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<!-- ## Uses
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pipeline_tag: text-classification
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# DELTA: Description Logics with Transformers
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Fine-tuning a transformer model for textual entailment over expressive contexts generated from description logic knowledge bases.
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Specifically, the model is given a context (a set of facts and rules) and a question.
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The model should answer with "True" if the question is logically implied from the context, "False" if it contradicts the context, and "Unknown" if none of the two.
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For more info please see our paper.
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## Model Details
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### Model Description
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DELTA<sub>M</sub> is a DeBERTaV3 large model fine-tuned on the DELTA<sub>D</sub> dataset.
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- **License:** MIT
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- **Finetuned from model:** `microsoft/deberta-v3-large`
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- **Repository:** https://github.com/angelosps/DELTA
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- **Paper:** [Transformers in the Service of Description Logic-based Contexts](https://arxiv.org/abs/2311.08941)
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<!-- ## Uses
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