diff --git a/optimum_benchmark/backends/pytorch/backend.py b/optimum_benchmark/backends/pytorch/backend.py
index 51070d8b..07e45980 100644
--- a/optimum_benchmark/backends/pytorch/backend.py
+++ b/optimum_benchmark/backends/pytorch/backend.py
@@ -308,7 +308,7 @@ def process_quantization_config(self) -> None:
 
         self.logger.info("\t+ Processing AutoQuantization config")
         self.quantization_config = AutoQuantizationConfig.from_dict(
-            getattr(self.pretrained_config, "quantization_config", {}).update(self.config.quantization_config)
+            (getattr(self.pretrained_config, "quantization_config") or {}).update(self.config.quantization_config)
         )
 
     @property
@@ -404,9 +404,9 @@ def forward(self, inputs: Dict[str, Any], kwargs: Dict[str, Any]) -> OrderedDict
 
     @torch.inference_mode()
     def prefill(self, inputs: Dict[str, Any], kwargs: Dict[str, Any]) -> OrderedDict:
-        assert kwargs.get("max_new_tokens") == kwargs.get("min_new_tokens") == 1, (
-            "For prefilling, max_new_tokens and min_new_tokens must be equal to 1"
-        )
+        assert (
+            kwargs.get("max_new_tokens") == kwargs.get("min_new_tokens") == 1
+        ), "For prefilling, max_new_tokens and min_new_tokens must be equal to 1"
         return self.pretrained_model.generate(**inputs, **kwargs)
 
     @torch.inference_mode()