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README.md

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 ## Sentence embeddings for English and Ancient Greek
 
-The HLM model architecture is based on [Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical Transformers](https://aclanthology.org/2024.sigtyp-1.16/) but uses a simpler architecture with rotary embeddings instead of using DeBERTa as a base architecture. This architecture produces superior results compared to the vanilla BERT architecture for low-resource languages like Ancient Greek. It is trained to produce sentence embeddings using the method described in [Sentence Embedding Models for Ancient Greek Using Multiligual Knowledge Distillation](https://aclanthology.org/2023.alp-1.2/).
+The HLM model architecture is based on [Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical Transformers](https://aclanthology.org/2024.sigtyp-1.16/) but uses a simpler architecture with rotary embeddings instead of using DeBERTa as a base architecture. This architecture produces superior results compared to the vanilla BERT architecture for low-resource languages like Ancient Greek. It is trained to produce sentence embeddings using the method described in [Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation](https://aclanthology.org/2023.alp-1.2/).
 
 This model was distilled from `BAAI/bge-base-en-v1.5` for embedding English and Ancient Greek text.