updated the interface as per comments

Author: amitsrivastava78

keras/src/models/model.py

@@ -8,6 +8,7 @@
 from keras.src.api_export import keras_export
 from keras.src.layers.layer import Layer
 from keras.src.models.variable_mapping import map_saveable_variables
+from keras.src.quantizers.gptq_config import GPTQConfig
 from keras.src.saving import saving_api
 from keras.src.trainers import trainer as base_trainer
 from keras.src.utils import summary_utils
@@ -420,7 +421,7 @@ def load_weights(self, filepath, skip_mismatch=False, **kwargs):
             **kwargs,
         )
 
-    def quantize(self, mode, **kwargs):
+    def quantize(self, mode, config=None, **kwargs):
         """Quantize the weights of the model.
 
         Note that the model must be built first before calling this method.
@@ -434,19 +435,22 @@ def quantize(self, mode, **kwargs):
         from keras.src.dtype_policies import QUANTIZATION_MODES
 
         if mode == "gptq":
-            from keras.src.quantizers.gptq_config import GPTQConfig
-
-            config = kwargs.get("quant_config")
             if not isinstance(config, GPTQConfig):
                 raise TypeError(
-                    "When using 'gptq' mode, you must pass a `quant_config` "
-                    "keyword argument of type `keras.quantizers.GPTQConfig`."
+                    "When using 'gptq' mode, you must pass a `config` "
+                    "argument of type `keras.quantizers.GPTQConfig`."
                 )
-
-            # The config object's own quantize method drives the process.
+            # The config object's own quantize method drives the process
             config.quantize(self)
             return
 
+        # For all other modes, verify that a config object was not passed.
+        if config is not None:
+            raise ValueError(
+                f"The `config` argument is only supported for 'gptq' mode, "
+                f"but received mode='{mode}'."
+            )
+
         type_check = kwargs.pop("type_check", True)
         if kwargs:
             raise ValueError(

keras/src/models/model_test.py

@@ -1334,7 +1334,7 @@ def _run_gptq_test_on_dataset(self, dataset, **config_kwargs):
         final_config = {**base_config, **config_kwargs}
         gptq_config = GPTQConfig(**final_config)
 
-        model.quantize("gptq", quant_config=gptq_config)
+        model.quantize("gptq", config=gptq_config)
 
         # Assertions and verification
         quantized_weights = target_layer.kernel