diff --git a/examples/community/lpw_stable_diffusion.py b/examples/community/lpw_stable_diffusion.py
index e912ad5244be..086cdf4844f7 100644
--- a/examples/community/lpw_stable_diffusion.py
+++ b/examples/community/lpw_stable_diffusion.py
@@ -10,11 +10,11 @@
 
 import diffusers
 from diffusers import SchedulerMixin, StableDiffusionPipeline
+from diffusers.loaders import TextualInversionLoaderMixin
 from diffusers.models import AutoencoderKL, UNet2DConditionModel
 from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput, StableDiffusionSafetyChecker
 from diffusers.utils import logging
 
-
 try:
     from diffusers.utils import PIL_INTERPOLATION
 except ImportError:
@@ -539,6 +539,11 @@ def _encode_prompt(
                 " the batch size of `prompt`."
             )
 
+        # textual inversion: process multi-vector tokens if necessary
+        if isinstance(self, TextualInversionLoaderMixin):
+            prompt = self.maybe_convert_prompt(prompt, self.tokenizer)
+            negative_prompt = self.maybe_convert_prompt(negative_prompt, self.tokenizer)
+
         text_embeddings, uncond_embeddings = get_weighted_text_embeddings(
             pipe=self,
             prompt=prompt,
diff --git a/examples/community/lpw_stable_diffusion_onnx.py b/examples/community/lpw_stable_diffusion_onnx.py
index e756097cb7c3..e04a691d7cd3 100644
--- a/examples/community/lpw_stable_diffusion_onnx.py
+++ b/examples/community/lpw_stable_diffusion_onnx.py
@@ -10,6 +10,7 @@
 
 import diffusers
 from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, SchedulerMixin
+from diffusers.loaders import TextualInversionLoaderMixin
 from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
 from diffusers.utils import logging
 
@@ -526,6 +527,11 @@ def _encode_prompt(
                 " the batch size of `prompt`."
             )
 
+        # textual inversion: process multi-vector tokens if necessary
+        if isinstance(self, TextualInversionLoaderMixin):
+            prompt = self.maybe_convert_prompt(prompt, self.tokenizer)
+            negative_prompt = self.maybe_convert_prompt(negative_prompt, self.tokenizer)
+
         text_embeddings, uncond_embeddings = get_weighted_text_embeddings(
             pipe=self,
             prompt=prompt,