diff --git a/src/refiners/foundationals/clip/concepts.py b/src/refiners/foundationals/clip/concepts.py
index 3b08765..3a7c99a 100644
--- a/src/refiners/foundationals/clip/concepts.py
+++ b/src/refiners/foundationals/clip/concepts.py
@@ -97,6 +97,8 @@ class ConceptExtender(fl.Chain, Adapter[CLIPTextEncoder]):
         with self.setup_adapter(target):
             super().__init__(target)
 
+        self._ensure_no_nesting()
+
         try:
             token_encoder, token_encoder_parent = next(target.walk(TokenEncoder))
             self._token_encoder_parent = [token_encoder_parent]
@@ -113,6 +115,11 @@ class ConceptExtender(fl.Chain, Adapter[CLIPTextEncoder]):
         self._embedding_extender = [EmbeddingExtender(token_encoder)]
         self._token_extender = [TokenExtender(clip_tokenizer)]
 
+    def _ensure_no_nesting(self) -> None:
+        assert not isinstance(
+            self.target.parent, ConceptExtender
+        ), "ConceptExtender cannot be nested, add concepts to the injected instance instead."
+
     @property
     def embedding_extender(self) -> EmbeddingExtender:
         assert len(self._embedding_extender) == 1, "EmbeddingExtender not found."
@@ -138,6 +145,7 @@ class ConceptExtender(fl.Chain, Adapter[CLIPTextEncoder]):
         self.token_extender.add_token(token, self.embedding_extender.num_embeddings - 1)
 
     def inject(self: "ConceptExtender", parent: fl.Chain | None = None) -> "ConceptExtender":
+        self._ensure_no_nesting()
         self.embedding_extender.inject(self.token_encoder_parent)
         self.token_extender.inject(self.clip_tokenizer_parent)
         return super().inject(parent)
diff --git a/tests/adapters/test_concept_extender.py b/tests/adapters/test_concept_extender.py
new file mode 100644
index 0000000..55c3599
--- /dev/null
+++ b/tests/adapters/test_concept_extender.py
@@ -0,0 +1,63 @@
+import pytest
+import torch
+
+from refiners.fluxion.utils import no_grad
+from refiners.foundationals.clip.concepts import ConceptExtender
+from refiners.foundationals.clip.text_encoder import CLIPTextEncoder, CLIPTextEncoderL
+from refiners.foundationals.clip.tokenizer import CLIPTokenizer
+
+
+@no_grad()
+@pytest.mark.parametrize("k_encoder", [CLIPTextEncoderL])
+def test_inject_eject(k_encoder: type[CLIPTextEncoder], test_device: torch.device):
+    encoder = k_encoder(device=test_device)
+    extender = ConceptExtender(encoder)
+
+    cat_embedding = torch.randn((encoder.embedding_dim,), device=test_device)
+    extender.add_concept(token="<token1>", embedding=cat_embedding)
+
+    extender_2 = ConceptExtender(encoder)
+
+    extender.inject()
+
+    with pytest.raises(AssertionError) as no_nesting:
+        extender_2.inject()
+    assert str(no_nesting.value) == "ConceptExtender cannot be nested, add concepts to the injected instance instead."
+
+    with pytest.raises(AssertionError) as no_nesting:
+        ConceptExtender(encoder)
+    assert str(no_nesting.value) == "ConceptExtender cannot be nested, add concepts to the injected instance instead."
+
+    dog_embedding = torch.randn((encoder.embedding_dim,), device=test_device)
+    extender.add_concept(token="<token2>", embedding=dog_embedding)
+    extender.eject()
+
+    extender_2.inject().eject()
+    ConceptExtender(encoder)  # no exception
+
+    tokenizer = encoder.ensure_find(CLIPTokenizer)
+    assert len(tokenizer.encode("<token1>")) > 3
+    assert len(tokenizer.encode("<token2>")) > 3
+
+    extender.inject()
+
+    tokenizer = encoder.ensure_find(CLIPTokenizer)
+    assert tokenizer.encode("<token1>").equal(
+        torch.tensor(
+            [
+                tokenizer.start_of_text_token_id,
+                tokenizer.end_of_text_token_id + 1,
+                tokenizer.end_of_text_token_id,
+            ]
+        )
+    )
+    assert tokenizer.encode("<token2>").equal(
+        torch.tensor(
+            [
+                tokenizer.start_of_text_token_id,
+                tokenizer.end_of_text_token_id + 2,
+                tokenizer.end_of_text_token_id,
+            ]
+        )
+    )
+    assert len(tokenizer.encode("<token3>")) > 3