Update README.md

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 Multilingual Knowledge Distillation](https://aclanthology.org/2023.alp-1.2/).
+This model creates sentence embeddings in a shared vector space for Ancient Greek and English text.
+
+The base model uses a modified version of the HLM architecture described in [Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical Transformers](https://aclanthology.org/2024.sigtyp-1.16/)
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+This model is trained to produce sentence embeddings using the multilingual knowledge distillation method and datasets 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.
 
 ## Usage (Sentence-Transformers)
 
-This model is currently incompatible with the latest version of the sentence-transformers library. For now, you must use this fork:
+**This model is currently incompatible with the latest version of the sentence-transformers library.**
+
+For now, either use HuggingFace Transformers directly (see below) or the following fork of sentence-transformers:
 https://github.com/kevinkrahn/sentence-transformers
 
-Then you can use the model like this:
+You can use the model with sentence-transformers like this:
 
 ```python
 from sentence_transformers import SentenceTransformer