From 288efddf2f6b8392dd74a0494b631c4d3b28304a Mon Sep 17 00:00:00 2001
From: Kohya S <52813779+kohya-ss@users.noreply.github.com>
Date: Thu, 6 Jul 2023 07:43:30 +0900
Subject: [PATCH] Update README.md

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

diff --git a/README.md b/README.md
index 53685c3f..7df0ec53 100644
--- a/README.md
+++ b/README.md
@@ -45,7 +45,7 @@ Summary of the feature:
   - Use `--cache_text_encoder_outputs` option and caching latents.
   - Use Adafactor optimizer. RMSprop 8bit or Adagrad 8bit may work. AdamW 8bit doesn't seem to work.
 - The LoRA training can be done with 12GB GPU memory.
-- `--train_unet_only` option is highly recommended for SDXL LoRA. Because SDXL has two text encoders, the result of the training will be unexpected.
+- `--network_train_unet_only` option is highly recommended for SDXL LoRA. Because SDXL has two text encoders, the result of the training will be unexpected.
 - PyTorch 2 seems to use slightly less GPU memory than PyTorch 1.
 
 Example of the optimizer settings for Adafactor with the fixed learning rate: