Update README.md

README.md

@@ -9,9 +9,15 @@ tags:
 
 # SBERT-base-nli-v2
 
-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 is used in "SGPT: GPT Sentence Embeddings for Semantic Search" and "TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning".
 
-This model is used in "TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning".
+## Usage
+
+For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt 
+
+## Evaluation Results
+
+For eval results, refer to our paper: https://arxiv.org/abs/2202.08904
 
 ## Usage (Sentence-Transformers)
 
@@ -125,4 +131,11 @@ SentenceTransformer(
 
 ## Citing & Authors
 
-<!--- Describe where people can find more information -->
+```bibtex
+@article{muennighoff2022sgpt,
+  title={SGPT: GPT Sentence Embeddings for Semantic Search},
+  author={Muennighoff, Niklas},
+  journal={arXiv preprint arXiv:2202.08904},
+  year={2022}
+}
+```