Add Aurora.load_checkpoint_local (#26)

* Add `Aurora.load_checkpoint_local`

* Propagate `strict`

aurora/model/aurora.py

@@ -225,10 +225,20 @@ def load_checkpoint(self, repo: str, name: str, strict: bool = True) -> None:
             strict (bool, optional): Error if the model parameters are not exactly equal to the
                 parameters in the checkpoint. Defaults to `True`.
         """
+        path = hf_hub_download(repo_id=repo, filename=name)
+        self.load_checkpoint_local(path, strict=strict)
+
+    def load_checkpoint_local(self, path: str, strict: bool = True) -> None:
+        """Load a checkpoint directly from a file.
+
+        Args:
+            path (str): Path to the checkpoint.
+            strict (bool, optional): Error if the model parameters are not exactly equal to the
+                parameters in the checkpoint. Defaults to `True`.
+        """
         # Assume that all parameters are either on the CPU or on the GPU.
         device = next(self.parameters()).device
 
-        path = hf_hub_download(repo_id=repo, filename=name)
         d = torch.load(path, map_location=device, weights_only=True)
 
         # Rename keys to ensure compatibility.