Add Gemma3 Conversion script to port weights from HF directly

keras_hub/src/models/gemma3/gemma3_causal_lm_preprocessor.py

@@ -283,9 +283,14 @@ def __init__(
         # is `None`.
         self.text_only_model = self.image_converter is None
 
-        self.image_placeholder = self.tokenizer.image_placeholder
-        self.start_of_image_token = self.tokenizer.start_of_image_token
-        self.end_of_image_token = self.tokenizer.end_of_image_token
+        if self.text_only_model:
+            self.image_placeholder = None
+            self.start_of_image_token = None
+            self.end_of_image_token = None
+        else:
+            self.image_placeholder = self.tokenizer.image_placeholder
+            self.start_of_image_token = self.tokenizer.start_of_image_token
+            self.end_of_image_token = self.tokenizer.end_of_image_token
 
     def build(self, input_shape):
         # Defer packer creation to `build()` so that we can be sure tokenizer

keras_hub/src/models/gemma3/gemma3_tokenizer.py

@@ -77,20 +77,32 @@ class Gemma3Tokenizer(SentencePieceTokenizer):
 
     backbone_cls = Gemma3Backbone
 
-    def __init__(self, proto, **kwargs):
+    def __init__(self, proto, is_vision_model=True, **kwargs):
         # Add special tokens.
 
+        self.is_vision_model = is_vision_model
         # The usual tokens.
         self._add_special_token("<bos>", "start_token")
         self._add_special_token("<eos>", "end_token")
         self._add_special_token("<pad>", "pad_token")
 
-        # Image placeholder token.
-        self._add_special_token("<img>", "image_placeholder")
-
-        #  Some tokens which are used in the preprocessor. We need to keep them
-        # here so that the preprocessor works with `tf.data`.
-        self._add_special_token("<start_of_image>", "start_of_image_token")
-        self._add_special_token("<end_of_image>", "end_of_image_token")
+        if is_vision_model:
+            # Image placeholder token.
+            self._add_special_token("<img>", "image_placeholder")
+            # Some tokens which are used in the preprocessor.
+            # We need to keep them
+            # here so that the preprocessor works with tf.data.
+            self._add_special_token("<start_of_image>", "start_of_image_token")
+            self._add_special_token("<end_of_image>", "end_of_image_token")
+        else:
+            # For text-only, skip assigning token IDs or set to -1
+            self.start_of_image_token_id = -1
+            self.image_placeholder_token_id = -1
+            self.end_of_image_token_id = -1
 
         super().__init__(proto=proto, **kwargs)
+
+    def get_config(self):
+        config = super().get_config()
+        config.update({"is_vision_model": self.is_vision_model})
+        return config