diff --git a/api/onnx_web/diffusers/utils.py b/api/onnx_web/diffusers/utils.py
index 0b8c6d47..7cc39875 100644
--- a/api/onnx_web/diffusers/utils.py
+++ b/api/onnx_web/diffusers/utils.py
@@ -10,6 +10,7 @@ from diffusers import OnnxStableDiffusionPipeline
 logger = getLogger(__name__)
 
 
+CLIP_TOKEN = compile(r"\<clip:([-\w]+):([\.|\d]+)\>")
 INVERSION_TOKEN = compile(r"\<inversion:([-\w]+):([\.|\d]+)\>")
 LORA_TOKEN = compile(r"\<lora:([-\w]+):([\.|\d]+)\>")
 MAX_TOKENS_PER_GROUP = 77
@@ -34,12 +35,16 @@ def expand_prompt(
     num_images_per_prompt: int,
     do_classifier_free_guidance: bool,
     negative_prompt: Optional[str] = None,
-    skip_clip_states: Optional[str] = 0,
+    skip_clip_states: Optional[int] = 0,
 ) -> "np.NDArray":
     # self provides:
     #   tokenizer: CLIPTokenizer
     #   encoder: OnnxRuntimeModel
 
+    prompt, clip_tokens = get_tokens_from_prompt(prompt, CLIP_TOKEN)
+    if len(clip_tokens) > 0:
+        skip_clip_states = int(clip_tokens[0][1])
+        logger.info("skipping %s CLIP layers", skip_clip_states)
 
     batch_size = len(prompt) if isinstance(prompt, list) else 1
     prompt = expand_prompt_ranges(prompt)