From 7e5df3c9fefbb85030ca2f467468c913ed75d838 Mon Sep 17 00:00:00 2001
From: Andrew Kane <andrew@ankane.org>
Date: Wed, 3 Apr 2024 23:36:43 -0700
Subject: [PATCH] Updated binary vectors section [skip ci]

---
 README.md | 22 +++++++---------------
 1 file changed, 7 insertions(+), 15 deletions(-)

diff --git a/README.md b/README.md
index 77444ed..ffc6dd6 100644
--- a/README.md
+++ b/README.md
@@ -421,9 +421,7 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
 
 ## Binary Vectors
 
-*Unreleased*
-
-Use the `bit` type to store binary vectors
+Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
 
 ```sql
 CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
@@ -432,6 +430,12 @@ INSERT INTO items (embedding) VALUES ('000'), ('111');
 
 Get the nearest neighbors by Hamming distance
 
+```sql
+SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
+```
+
+Or (unreleased)
+
 ```sql
 SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
 ```
@@ -678,18 +682,6 @@ and query with:
 SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
 ```
 
-#### Are binary vectors supported?
-
-You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
-
-```tsql
-CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
-INSERT INTO items (embedding) VALUES ('000'), ('111');
-SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
-```
-
-Indexing is not currently supported.
-
 #### Do indexes need to fit into memory?
 
 No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with: