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@@ -95,10 +95,9 @@ parent_norms = model.manifold.dist0(parent_entity_embeddings)
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  subsumption_scores = - (dists + centri_score_weight * (parent_norms - child_norms))
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  ```
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- Training and evaluation scripts are available at [GitHub](https://github.com/KRR-Oxford/HierarchyTransformers/tree/main/scripts). See `scripts/evaluate.py` for how we determine the hyperparameters on the validation set for subsumption prediction.
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- Technical details are presented in the [paper](https://arxiv.org/abs/2401.11374).
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  ## Full Model Architecture
 
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  subsumption_scores = - (dists + centri_score_weight * (parent_norms - child_norms))
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  ```
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+ ### Train Your Own Models
 
 
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+ Use the scripts in our [repo]((https://github.com/KRR-Oxford/HierarchyTransformers/tree/main/scripts)) to reproduce existing models and train/evaluate your own models.
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  ## Full Model Architecture