Update README.md

README.md

@@ -20,13 +20,11 @@ language:
 
 <img src="https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/38Yc1IgU4bH92Wyb43J2I.png" alt="image/png" style="max-width: 75%;">
 
-This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
-
-- this model's primary use case is meant to be long-document similarity, i.e. computing embeddings of long documents and comparing those.
-  - check out the training dataset `pszemraj/synthetic-text-similarity` for details
-- pretrained & finetuned at context length 16384
-- This model is a "v1" and we may make improved versions in the future. Or, we may not.
-
+This [Sentence Transformer Model] (https://www.SBERT.net) converts sentences and paragraphs into a 768-dimensional vector space suitable for tasks such as clustering and semantic search.
+  - This model focuses on the similarity of long documents; use it for comparing embeddings of long text documents
+  - For more info, see the `pszemraj/synthetic-text-similarity` dataset used for training
+- Pre-trained and tuned for a context length of 16,384
+- This initial version may be updated in the future.
 
 ## Usage