diff --git a/README.md b/README.md
index 590b011..ee96872 100644
--- a/README.md
+++ b/README.md
@@ -15,6 +15,8 @@ For SDXL, you only need the LoRA (as far as I know) so a dedicated node is unnec
 * Put the `resolution_normalization.safetensors` model in `models/unet`
 * Patch the model with the `ApplyResAdapterUnet` node, load the `resolution_lora.safetensors` LoRA normally.
 
+![Node example](assets/applynode.png)
+
 You can experiment with different unet and LoRA strengths.
 I haven't tested it extensively, but at resolutions above 1024x1024 using full strength doesn't seem to work well (and in fact may be worse than nothing).
 It's also possible to combine ResAdapter with other techniques such as Kohya Deep Shrink (AKA `PatchModelAddDownScale`).
diff --git a/assets/applynode.png b/assets/applynode.png
new file mode 100644
index 0000000..9301fba
Binary files /dev/null and b/assets/applynode.png differ