diff --git a/examples/dreambooth/train_dreambooth_flax.py b/examples/dreambooth/train_dreambooth_flax.py
index 84493b1d9484..078a66e4acee 100644
--- a/examples/dreambooth/train_dreambooth_flax.py
+++ b/examples/dreambooth/train_dreambooth_flax.py
@@ -452,7 +452,9 @@ def collate_fn(examples):
         weight_dtype = jnp.bfloat16
 
     # Load models and create wrapper for stable diffusion
-    text_encoder = FlaxCLIPTextModel.from_pretrained("openai/clip-vit-large-patch14", dtype=weight_dtype)
+    text_encoder = FlaxCLIPTextModel.from_pretrained(
+        args.pretrained_model_name_or_path, subfolder="text_encoder", dtype=weight_dtype
+    )
     vae, vae_params = FlaxAutoencoderKL.from_pretrained(
         args.pretrained_model_name_or_path, subfolder="vae", dtype=weight_dtype
     )
diff --git a/examples/text_to_image/train_text_to_image_flax.py b/examples/text_to_image/train_text_to_image_flax.py
index cacfacef498b..89a8dec7289e 100644
--- a/examples/text_to_image/train_text_to_image_flax.py
+++ b/examples/text_to_image/train_text_to_image_flax.py
@@ -379,7 +379,9 @@ def collate_fn(examples):
 
     # Load models and create wrapper for stable diffusion
     tokenizer = CLIPTokenizer.from_pretrained(args.pretrained_model_name_or_path, subfolder="tokenizer")
-    text_encoder = FlaxCLIPTextModel.from_pretrained("openai/clip-vit-large-patch14", dtype=weight_dtype)
+    text_encoder = FlaxCLIPTextModel.from_pretrained(
+        args.pretrained_model_name_or_path, subfolder="text_encoder", dtype=weight_dtype
+    )
     vae, vae_params = FlaxAutoencoderKL.from_pretrained(
         args.pretrained_model_name_or_path, subfolder="vae", dtype=weight_dtype
     )
diff --git a/examples/textual_inversion/textual_inversion_flax.py b/examples/textual_inversion/textual_inversion_flax.py
index 84ff97c39a96..be2b7ffb5490 100644
--- a/examples/textual_inversion/textual_inversion_flax.py
+++ b/examples/textual_inversion/textual_inversion_flax.py
@@ -391,7 +391,7 @@ def main():
     placeholder_token_id = tokenizer.convert_tokens_to_ids(args.placeholder_token)
 
     # Load models and create wrapper for stable diffusion
-    text_encoder = FlaxCLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
+    text_encoder = FlaxCLIPTextModel.from_pretrained(args.pretrained_model_name_or_path, subfolder="text_encoder")
     vae, vae_params = FlaxAutoencoderKL.from_pretrained(args.pretrained_model_name_or_path, subfolder="vae")
     unet, unet_params = FlaxUNet2DConditionModel.from_pretrained(args.pretrained_model_name_or_path, subfolder="unet")