diff --git a/nerfstudio/engine/trainer.py b/nerfstudio/engine/trainer.py
index a653e1de8d..7f2f0d34d0 100644
--- a/nerfstudio/engine/trainer.py
+++ b/nerfstudio/engine/trainer.py
@@ -429,7 +429,7 @@ def _load_checkpoint(self) -> None:
                 load_step = sorted(int(x[x.find("-") + 1 : x.find(".")]) for x in os.listdir(load_dir))[-1]
             load_path: Path = load_dir / f"step-{load_step:09d}.ckpt"
             assert load_path.exists(), f"Checkpoint {load_path} does not exist"
-            loaded_state = torch.load(load_path, map_location="cpu")
+            loaded_state = torch.load(load_path, map_location="cpu", weights_only=False)
             self._start_step = loaded_state["step"] + 1
             # load the checkpoints for pipeline, optimizers, and gradient scalar
             self.pipeline.load_pipeline(loaded_state["pipeline"], loaded_state["step"])
@@ -440,7 +440,7 @@ def _load_checkpoint(self) -> None:
             CONSOLE.print(f"Done loading Nerfstudio checkpoint from {load_path}")
         elif load_checkpoint is not None:
             assert load_checkpoint.exists(), f"Checkpoint {load_checkpoint} does not exist"
-            loaded_state = torch.load(load_checkpoint, map_location="cpu")
+            loaded_state = torch.load(load_checkpoint, map_location="cpu", weights_only=False)
             self._start_step = loaded_state["step"] + 1
             # load the checkpoints for pipeline, optimizers, and gradient scalar
             self.pipeline.load_pipeline(loaded_state["pipeline"], loaded_state["step"])
diff --git a/nerfstudio/scripts/downloads/download_data.py b/nerfstudio/scripts/downloads/download_data.py
index a2c9d27584..653fbf94d0 100644
--- a/nerfstudio/scripts/downloads/download_data.py
+++ b/nerfstudio/scripts/downloads/download_data.py
@@ -514,7 +514,7 @@ def download(self, save_dir: Path) -> None:
             split_filepaths = []
             for image_path, new_image_path in copied_images.items():
                 metadata_path = image_path.parent.parent / "metadata" / f"{image_path.stem}.pt"
-                metadata = torch.load(metadata_path, map_location="cpu")
+                metadata = torch.load(metadata_path, map_location="cpu", weights_only=False)
                 c2w = torch.eye(4)
                 c2w[:3] = metadata["c2w"]
                 file_path = str(Path("images") / f"{new_image_path.name}")
diff --git a/nerfstudio/utils/eval_utils.py b/nerfstudio/utils/eval_utils.py
index 11a8b23416..8d07fe842a 100644
--- a/nerfstudio/utils/eval_utils.py
+++ b/nerfstudio/utils/eval_utils.py
@@ -59,7 +59,7 @@ def eval_load_checkpoint(config: TrainerConfig, pipeline: Pipeline) -> Tuple[Pat
         load_step = config.load_step
     load_path = config.load_dir / f"step-{load_step:09d}.ckpt"
     assert load_path.exists(), f"Checkpoint {load_path} does not exist"
-    loaded_state = torch.load(load_path, map_location="cpu")
+    loaded_state = torch.load(load_path, map_location="cpu", weights_only=False)
     pipeline.load_pipeline(loaded_state["pipeline"], loaded_state["step"])
     CONSOLE.print(f":white_check_mark: Done loading checkpoint from {load_path}")
     return load_path, load_step