From 3178fef8a0b845bf5971bd3ead3894fcf001f1a3 Mon Sep 17 00:00:00 2001
From: Han Xiao <artex.xh@gmail.com>
Date: Sun, 3 Jan 2021 17:51:29 +0100
Subject: [PATCH] docs: update readme

---
 README.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index b8c42cd441918..795a716340766 100644
--- a/README.md
+++ b/README.md
@@ -234,10 +234,11 @@ To add logic to the Flow, use the `uses` parameter to attach a Pod with an [Exec
 
 ```python
 f = (Flow().add(uses='MyBertEncoder')  # class name of a Jina Executor
-           .add(uses='jinahub/pretrained-cnn:latest')  # Dockerized Jina Pod
+           .add(uses='docker://jinahub/pretrained-cnn:latest')  # the container name
            .add(uses='myencoder.yaml')  # YAML serialization of a Jina Executor
            .add(uses='!WaveletTransformer | {freq: 20}')  # inline YAML config
            .add(uses='_pass'))  # built-in shortcut executor
+           .add(uses={'__cls': 'MyBertEncoder', 'with': {'param': 1.23}})  # dict config object with __cls keyword
 ```
 
 The power of Jina lies in its decentralized architecture: each `add` creates a new Pod, and these Pods can be run as a local thread/process, a remote process, inside a Docker container, or even inside a remote Docker container.