diff --git a/README.md b/README.md
index 50cf01d..a8e1c95 100644
--- a/README.md
+++ b/README.md
@@ -50,7 +50,7 @@ Training a RAVE model usually involves 3 separate steps, namely _dataset prepara
 You can know prepare a dataset using two methods: regular and lazy. Lazy preprocessing allows RAVE to be trained directly on the raw files (i.e. mp3, ogg), without converting them first. **Warning**: lazy dataset loading will increase your CPU load by a large margin during training, especially on Windows. This can however be useful when training on large audio corpus which would not fit on a hard drive when uncompressed. In any case, prepare your dataset using
 
 ```bash
-rave preprocess --input_path /audio/folder --output_path /dataset/path (--lazy)
+rave preprocess --input_path /audio/folder --output_path /dataset/path --channels X (--lazy)
 ```
 
 ### Training