Initial Kaggle upload.

keras_nlp/__init__.py

@@ -26,5 +26,6 @@
 from keras_nlp import samplers
 from keras_nlp import tokenizers
 from keras_nlp import utils
+from keras_nlp.utils import upload_preset
 from keras_nlp.version_utils import __version__
 from keras_nlp.version_utils import version

keras_nlp/models/backbone.py

@@ -17,6 +17,7 @@
 from keras_nlp.backend import keras
 from keras_nlp.utils.preset_utils import check_preset_class
 from keras_nlp.utils.preset_utils import load_from_preset
+from keras_nlp.utils.preset_utils import save_to_preset
 from keras_nlp.utils.python_utils import classproperty
 from keras_nlp.utils.python_utils import format_docstring
 
@@ -141,6 +142,12 @@ def from_preset(
             config_overrides=kwargs,
         )
 
+    def save_to_preset(
+        self,
+        preset,
+    ):
+        save_to_preset(self, preset)
+
     def __init_subclass__(cls, **kwargs):
         # Use __init_subclass__ to setup a correct docstring for from_preset.
         super().__init_subclass__(**kwargs)

keras_nlp/models/preprocessor.py

@@ -18,6 +18,7 @@
 )
 from keras_nlp.utils.preset_utils import check_preset_class
 from keras_nlp.utils.preset_utils import load_from_preset
+from keras_nlp.utils.preset_utils import save_to_preset
 from keras_nlp.utils.python_utils import classproperty
 from keras_nlp.utils.python_utils import format_docstring
 
@@ -96,6 +97,13 @@ def from_preset(
         )
         return cls(tokenizer=tokenizer, **kwargs)
 
+    def save_to_preset(
+        self,
+        preset,
+        config_filename="tokenizer.json",
+    ):
+        save_to_preset(self, preset, config_filename=config_filename)
+
     def __init_subclass__(cls, **kwargs):
         # Use __init_subclass__ to setup a correct docstring for from_preset.
         super().__init_subclass__(**kwargs)

keras_nlp/models/task.py

@@ -23,6 +23,7 @@
 from keras_nlp.utils.pipeline_model import PipelineModel
 from keras_nlp.utils.preset_utils import check_preset_class
 from keras_nlp.utils.preset_utils import load_from_preset
+from keras_nlp.utils.preset_utils import save_to_preset
 from keras_nlp.utils.python_utils import classproperty
 from keras_nlp.utils.python_utils import format_docstring
 
@@ -253,6 +254,12 @@ def from_preset(
             config_overrides=kwargs,
         )
 
+    def save_to_preset(
+        self,
+        preset,
+    ):
+        save_to_preset(self, preset)
+
     def __init_subclass__(cls, **kwargs):
         # Use __init_subclass__ to setup a correct docstring for from_preset.
         super().__init_subclass__(**kwargs)

keras_nlp/tokenizers/tokenizer.py

@@ -18,6 +18,7 @@
 from keras_nlp.layers.preprocessing.preprocessing_layer import (
     PreprocessingLayer,
 )
+from keras_nlp.utils.preset_utils import save_to_preset
 
 
 @keras_nlp_export("keras_nlp.tokenizers.Tokenizer")
@@ -121,5 +122,12 @@ def token_to_id(self, token: str) -> int:
             f"{self.__class__.__name__}."
         )
 
+    def save_to_preset(
+        self,
+        preset,
+        config_filename="tokenizer.json",
+    ):
+        save_to_preset(self, preset, config_filename=config_filename)
+
     def call(self, inputs, *args, training=None, **kwargs):
         return self.tokenize(inputs, *args, **kwargs)

keras_nlp/utils/__init__.py

@@ -11,3 +11,4 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from keras_nlp.utils.preset_utils import upload_preset

keras_nlp/utils/preset_utils.py

@@ -155,6 +155,20 @@ def save_to_preset(
             metadata_file.write(json.dumps(metadata, indent=4))
 
 
+def upload_preset(
+    preset,
+    uri,
+):
+    if uri.startswith(KAGGLE_PREFIX):
+        kaggle_handle = uri.removeprefix(KAGGLE_PREFIX)
+        kagglehub.model_upload(kaggle_handle, preset)
+    else:
+        raise ValueError(
+            f"Unexpected URI `'{uri}'`. "
+            f"URI prefix should be one of `'{','.join([KAGGLE_PREFIX])}'`."
+        )
+
+
 def load_from_preset(
     preset,
     load_weights=True,