diff --git a/keras_nlp/models/f_net/f_net_tokenizer.py b/keras_nlp/models/f_net/f_net_tokenizer.py
index ed1e1cf011..9a19330f12 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer.py
@@ -15,15 +15,11 @@
 """FNet tokenizer."""
 
 import copy
-import os
-
-from tensorflow import keras
 
 from keras_nlp.api_export import keras_nlp_export
 from keras_nlp.models.f_net.f_net_presets import backbone_presets
 from keras_nlp.tokenizers.sentence_piece_tokenizer import SentencePieceTokenizer
 from keras_nlp.utils.python_utils import classproperty
-from keras_nlp.utils.python_utils import format_docstring
 
 
 @keras_nlp_export("keras_nlp.models.FNetTokenizer")
@@ -92,52 +88,3 @@ def __init__(self, proto, **kwargs):
     @classproperty
     def presets(cls):
         return copy.deepcopy(backbone_presets)
-
-    @classmethod
-    @format_docstring(names=", ".join(backbone_presets))
-    def from_preset(
-        cls,
-        preset,
-        **kwargs,
-    ):
-        """Instantiate an FNet tokenizer from preset vocabulary.
-
-        Args:
-            preset: string. Must be one of {{names}}.
-
-        Examples:
-        ```python
-        # Load a preset tokenizer.
-        tokenizer = keras_nlp.models.FNetTokenizer.from_preset(
-            "f_net_base_en",
-        )
-
-        # Tokenize some input.
-        tokenizer("The quick brown fox tripped.")
-
-        # Detokenize some input.
-        tokenizer.detokenize([5, 6, 7, 8, 9])
-        ```
-        """
-        if preset not in cls.presets:
-            raise ValueError(
-                "`preset` must be one of "
-                f"""{", ".join(cls.presets)}. Received: {preset}."""
-            )
-        metadata = cls.presets[preset]
-
-        spm_proto = keras.utils.get_file(
-            "vocab.spm",
-            metadata["spm_proto_url"],
-            cache_subdir=os.path.join("models", preset),
-            file_hash=metadata["spm_proto_hash"],
-        )
-
-        config = metadata["preprocessor_config"]
-        config.update(
-            {
-                "proto": spm_proto,
-            },
-        )
-
-        return cls.from_config({**config, **kwargs})