From 7594ed3b7cbe0d6ed9791f253ece2ef88ea2c313 Mon Sep 17 00:00:00 2001
From: Sean MacAvaney <sean.macavaney@gmail.com>
Date: Wed, 27 Nov 2024 20:50:13 +0000
Subject: [PATCH] docs

---
 pyterrier_dr/pt_docs/index.rst | 1 +
 pyterrier_dr/pt_docs/sbert.rst | 3 ++-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/pyterrier_dr/pt_docs/index.rst b/pyterrier_dr/pt_docs/index.rst
index e6dfc55..92328c2 100644
--- a/pyterrier_dr/pt_docs/index.rst
+++ b/pyterrier_dr/pt_docs/index.rst
@@ -42,3 +42,4 @@ Import ``pyterrier_dr``, load a pre-built index and model, and retrieve:
     :maxdepth: 1
 
     prf
+    sbert
diff --git a/pyterrier_dr/pt_docs/sbert.rst b/pyterrier_dr/pt_docs/sbert.rst
index 73e0957..fb32ea7 100644
--- a/pyterrier_dr/pt_docs/sbert.rst
+++ b/pyterrier_dr/pt_docs/sbert.rst
@@ -1,7 +1,8 @@
 Using Sentence Transformer models for Dense retrieval in PyTerrier
 ==================================================================
 
-With PyTerrier_DR, its easy to support Sentence Transformer models, e.g. from HuggingFace, for dense retrieval.
+With PyTerrier_DR, its easy to support Sentence Transformer (formerly called SentenceBERT)
+models, e.g. from HuggingFace, for dense retrieval.
 
 The base class is ``SBertBiEncoder('huggingface/path')``;