Update README.md

README.md

@@ -5,7 +5,7 @@ datasets:
 tags:
 - esmc
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-# ProtHash
+# ESMC ProtHash
 
 A protein language model that outputs amino acid sequence embeddings for use in clustering, classification, locality-sensitive hashing, and more. Distilled from the [ESMC](https://www.evolutionaryscale.ai/blog/esm-cambrian) family of models, ProtHash produces contextual embeddings that align in vector space according to the sequences' underlying biological properties such as structure and function. Trained on the [SwissProt](https://huggingface.co/datasets/andrewdalpino/SwissProt-Gene-Ontology) dataset to mimic the activations of its ESMC teacher model, ProtHash embeddings have near-perfect similarity to ESMC embeddings but at a greatly reduced computational cost.
 
@@ -13,7 +13,7 @@ A protein language model that outputs amino acid sequence embeddings for use in
 
 - **Blazing fast and efficient**: ProtHash uses as few as 1.5% of its ESMC teacher's total parameters to achieve near-perfect cosine similarity between the two embedding spaces.
 
-- **Biologically-relevant**: Biologically similar proteins will show up nearby in the embedding space enabling downstream tasks such as clustering, classification, and locality-sensitive hashing based on atomic structure.
+- **Biologically-relevant**: Biologically similar proteins will show up nearby in the embedding space enabling downstream tasks such as clustering, classification, and locality-sensitive hashing.
 
 - **Compatible with ESMC**: ProtHash can output embeddings in its native or ESMC teacher's dimensionality - allowing it to serve as either a faster drop-in approximation to ESMC embeddings or a more efficient compressed representation.