diff --git a/keras_cv/models/feature_extractor/clip/clip_processor.py b/keras_cv/models/feature_extractor/clip/clip_processor.py
index 1771e05ffa..1a07a3d710 100644
--- a/keras_cv/models/feature_extractor/clip/clip_processor.py
+++ b/keras_cv/models/feature_extractor/clip/clip_processor.py
@@ -23,6 +23,7 @@
 except ImportError:
     keras_nlp = None
 
+
 @keras_cv_export("keras_cv.models.feature_extractor.CLIPProcessor")
 class CLIPProcessor:
     """
diff --git a/keras_cv/models/feature_extractor/clip/clip_tokenizer.py b/keras_cv/models/feature_extractor/clip/clip_tokenizer.py
index 9219d7cf15..c0aab3cfa0 100644
--- a/keras_cv/models/feature_extractor/clip/clip_tokenizer.py
+++ b/keras_cv/models/feature_extractor/clip/clip_tokenizer.py
@@ -149,8 +149,9 @@ def process_unseen_tokens():
                 self._bpe_merge_and_update_cache(unseen_tokens)
                 return self.cache.lookup(flat_tokens)
 
-            # If `has_unseen_words == True`, it means not all tokens are in cache,
-            # we will process the unseen tokens. Otherwise return the cache lookup.
+            # If `has_unseen_words == True`, it means not all tokens are,
+            # in cache we will process the unseen tokens. Otherwise
+            # return the cache lookup.
             tokenized_words = tf.cond(
                 has_unseen_words,
                 process_unseen_tokens,
diff --git a/keras_cv/utils/conditional_imports.py b/keras_cv/utils/conditional_imports.py
index 0f0ea2b890..2ae1ec88b0 100644
--- a/keras_cv/utils/conditional_imports.py
+++ b/keras_cv/utils/conditional_imports.py
@@ -83,4 +83,4 @@ def assert_keras_nlp_installed(symbol_name):
             f"{symbol_name} requires the `keras_nlp` package. "
             "Please install the package using "
             "`pip install keras_nlp`."
-        )
\ No newline at end of file
+        )