Update README.md

README.md

@@ -99,7 +99,7 @@ model_description: "Language model for embedding organismal trait descriptions.
 
 # Model Card for Trait2Vec
 
-Trait2Vec is a language model to embed organismal trait descriptions in a way that preserves the structure induced by a semantic similarity metric (e.g. SimGIC). The model was trained on the [char-sim-data](https://huggingface.co/datasets/imageomics/char-sim-data) dataset. It is fine-tuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). This was removed, should it have been?>>>It maps sentences & paragraphs to a 256-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+Trait2Vec is a language model to embed organismal trait descriptions in a way that preserves the structure induced by a semantic similarity metric (e.g. SimGIC). The model was trained on the [char-sim-data](https://huggingface.co/datasets/imageomics/char-sim-data) dataset. It is fine-tuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). 
 Through qualitative data exploration we observe the cosine similarity between embeddings of raw trait description is proportional to the semantic similarity of their corresponding ontological representations. 
 
 ## Model Details