diff --git a/src/diffusers/loaders.py b/src/diffusers/loaders.py
index b4c443fd303b..8878fb116d1d 100644
--- a/src/diffusers/loaders.py
+++ b/src/diffusers/loaders.py
@@ -410,7 +410,7 @@ def _maybe_convert_prompt(self, prompt: str, tokenizer: "PreTrainedTokenizer"):
                 replacement = token
                 i = 1
                 while f"{token}_{i}" in tokenizer.added_tokens_encoder:
-                    replacement += f"{token}_{i}"
+                    replacement += f" {token}_{i}"
                     i += 1
 
                 prompt = prompt.replace(token, replacement)
diff --git a/tests/pipelines/test_pipelines.py b/tests/pipelines/test_pipelines.py
index a5d70b01d453..8fb79f0c4057 100644
--- a/tests/pipelines/test_pipelines.py
+++ b/tests/pipelines/test_pipelines.py
@@ -541,7 +541,7 @@ def test_text_inversion_download(self):
             assert pipe.text_encoder.get_input_embeddings().weight[-3].sum().item() == 96
             assert pipe.text_encoder.get_input_embeddings().weight[-2].sum().item() == 128
             assert pipe.text_encoder.get_input_embeddings().weight[-1].sum().item() == 160
-            assert pipe._maybe_convert_prompt("<***>", pipe.tokenizer) == "<***><***>_1<***>_2"
+            assert pipe._maybe_convert_prompt("<***>", pipe.tokenizer) == "<***> <***>_1 <***>_2"
 
             prompt = "hey <***>"
             out = pipe(prompt, num_inference_steps=1, output_type="numpy").images
@@ -569,7 +569,7 @@ def test_text_inversion_download(self):
             assert pipe.text_encoder.get_input_embeddings().weight[-3].sum().item() == 96
             assert pipe.text_encoder.get_input_embeddings().weight[-2].sum().item() == 128
             assert pipe.text_encoder.get_input_embeddings().weight[-1].sum().item() == 160
-            assert pipe._maybe_convert_prompt("<****>", pipe.tokenizer) == "<****><****>_1<****>_2"
+            assert pipe._maybe_convert_prompt("<****>", pipe.tokenizer) == "<****> <****>_1 <****>_2"
 
             prompt = "hey <****>"
             out = pipe(prompt, num_inference_steps=1, output_type="numpy").images