From f6db9c80e413bed39c721cee9b5bcaecf39ef50b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Philippe=20R=C3=A9my?= <premy.enseirb@gmail.com>
Date: Sun, 19 Mar 2023 10:33:21 +0700
Subject: [PATCH] Update README.md

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index cee8dbd..dbec419 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@
 [![license](https://img.shields.io/badge/License-Apache_2.0-brightgreen.svg)](https://github.com/philipperemy/keras-attention-mechanism/blob/master/LICENSE) [![dep1](https://img.shields.io/badge/Tensorflow-2.0+-brightgreen.svg)](https://www.tensorflow.org/)
 ![Simple Keras Attention CI](https://github.com/philipperemy/keras-attention-mechanism/workflows/Simple%20Keras%20Attention%20CI/badge.svg)
 
-Many-to-one attention mechanism for Keras.
+Attention Layer for Keras. Supports the score functions of Luong and Bahdanau.
 
 <p align="center">
   <img src="examples/equations.png" width="600">
@@ -34,7 +34,7 @@ Attention(
 
 ### Arguments
 
-- `units`: Integer. The number of units in the attention vector ($a_t$).
+- `units`: Integer. The number of (output) units in the attention vector ($a_t$).
 - `score`: String. The score function $score(h_t, \bar{h_s})$. Possible values are `luong` or `bahdanau`.