diff --git a/examples/text_to_image/README.md b/examples/text_to_image/README.md
index d51a04414137..788c021b77f5 100644
--- a/examples/text_to_image/README.md
+++ b/examples/text_to_image/README.md
@@ -191,7 +191,7 @@ In a nutshell, LoRA allows adapting pretrained models by adding pairs of rank-de
 
 - Previous pretrained weights are kept frozen so that model is not prone to [catastrophic forgetting](https://www.pnas.org/doi/10.1073/pnas.1611835114).
 - Rank-decomposition matrices have significantly fewer parameters than original model, which means that trained LoRA weights are easily portable.
-- LoRA attention layers allow to control to which extent the model is adapted toward new training images via a `scale` parameter.
+- LoRA attention layers allow controlling to which extent the model is adapted toward new training images via a `scale` parameter.
 
 [cloneofsimo](https://github.com/cloneofsimo) was the first to try out LoRA training for Stable Diffusion in the popular [lora](https://github.com/cloneofsimo/lora) GitHub repository.