diff --git a/fastembed/text/custom_text_embedding.py b/fastembed/text/custom_text_embedding.py
index 465ffd251..b3a7db147 100644
--- a/fastembed/text/custom_text_embedding.py
+++ b/fastembed/text/custom_text_embedding.py
@@ -50,8 +50,9 @@ def __init__(
             specific_model_path=specific_model_path,
             **kwargs,
         )
-        self._pooling = self.POSTPROCESSING_MAPPING[model_name].pooling
-        self._normalization = self.POSTPROCESSING_MAPPING[model_name].normalization
+        postprocessing_config = self.POSTPROCESSING_MAPPING[self.model_description.model]
+        self._pooling = postprocessing_config.pooling
+        self._normalization = postprocessing_config.normalization
 
     @classmethod
     def _list_supported_models(cls) -> list[DenseModelDescription]:
diff --git a/tests/test_custom_models.py b/tests/test_custom_models.py
index dcca7d89c..f3a14e891 100644
--- a/tests/test_custom_models.py
+++ b/tests/test_custom_models.py
@@ -21,9 +21,11 @@
 @pytest.fixture(autouse=True)
 def restore_custom_models_fixture():
     CustomTextEmbedding.SUPPORTED_MODELS = []
+    CustomTextEmbedding.POSTPROCESSING_MAPPING = {}
     CustomTextCrossEncoder.SUPPORTED_MODELS = []
     yield
     CustomTextEmbedding.SUPPORTED_MODELS = []
+    CustomTextEmbedding.POSTPROCESSING_MAPPING = {}
     CustomTextCrossEncoder.SUPPORTED_MODELS = []
 
 
@@ -74,9 +76,6 @@ def test_text_custom_model():
     if is_ci:
         delete_model_cache(model.model._model_dir)
 
-    CustomTextEmbedding.SUPPORTED_MODELS.clear()
-    CustomTextEmbedding.POSTPROCESSING_MAPPING.clear()
-
 
 def test_cross_encoder_custom_model():
     is_ci = os.getenv("CI")
@@ -114,8 +113,6 @@ def test_cross_encoder_custom_model():
     if is_ci:
         delete_model_cache(model.model._model_dir)
 
-    CustomTextCrossEncoder.SUPPORTED_MODELS.clear()
-
 
 def test_mock_add_custom_models():
     dim = 5
@@ -175,8 +172,24 @@ def test_mock_add_custom_models():
         )
         assert np.allclose(post_processed_output, expected_output[model_name], atol=1e-3)
 
-    CustomTextEmbedding.SUPPORTED_MODELS.clear()
-    CustomTextEmbedding.POSTPROCESSING_MAPPING.clear()
+
+def test_custom_text_model_lookup_is_case_insensitive():
+    model_name = "Org/Model"
+
+    TextEmbedding.add_custom_model(
+        model_name,
+        pooling=PoolingType.MEAN,
+        normalization=True,
+        sources=ModelSource(hf="artificial"),
+        dim=5,
+        size_in_gb=0.1,
+    )
+
+    model = TextEmbedding("org/model", lazy_load=True, specific_model_path="./")
+
+    assert isinstance(model.model, CustomTextEmbedding)
+    assert model.model._pooling == PoolingType.MEAN
+    assert model.model._normalization is True
 
 
 def test_do_not_add_existing_model():
@@ -212,9 +225,6 @@ def test_do_not_add_existing_model():
             size_in_gb=0.47,
         )
 
-    CustomTextEmbedding.SUPPORTED_MODELS.clear()
-    CustomTextEmbedding.POSTPROCESSING_MAPPING.clear()
-
 
 def test_do_not_add_existing_cross_encoder():
     existing_base_model = "Xenova/ms-marco-MiniLM-L-6-v2"
@@ -239,5 +249,3 @@ def test_do_not_add_existing_cross_encoder():
             sources=ModelSource(hf=custom_model_name),
             size_in_gb=0.08,
         )
-
-    CustomTextCrossEncoder.SUPPORTED_MODELS.clear()