diff --git a/onnxscript/ir/__init__.py b/onnxscript/ir/__init__.py
index 80df83bbf..b9266ea1f 100644
--- a/onnxscript/ir/__init__.py
+++ b/onnxscript/ir/__init__.py
@@ -71,6 +71,9 @@
     # Pass infrastructure
     "passes",
     "traversal",
+    # IO
+    "load",
+    "save",
 ]
 
 from onnxscript.ir import passes, serde, traversal
@@ -114,6 +117,7 @@
     AttributeType,
     DataType,
 )
+from onnxscript.ir._io import load, save
 from onnxscript.ir._protocols import (
     ArrayCompatible,
     AttributeProtocol,
diff --git a/onnxscript/ir/_core.py b/onnxscript/ir/_core.py
index b5a29cdd4..f1f5c9350 100644
--- a/onnxscript/ir/_core.py
+++ b/onnxscript/ir/_core.py
@@ -475,6 +475,8 @@ class ExternalTensor(TensorBase, _protocols.TensorProtocol):  # pylint: disable=
 
     Attributes:
         path: The path to the data file. This can be a relative path or an absolute path.
+        base_dir: The base directory for the external data. It is used to resolve relative paths.
+            At serialization, only the ``path`` is serialized into the "location" field of the TensorProto.
         offset: The offset in bytes from the start of the file.
         length: The length of the data in bytes.
         dtype: The data type of the tensor.
@@ -509,8 +511,15 @@ def __init__(
         name: str,
         doc_string: str | None = None,
         metadata_props: dict[str, str] | None = None,
+        base_dir: os.PathLike | str = "",
     ) -> None:
-        self._path = path
+        if os.path.isabs(path):
+            self._base_dir = os.path.dirname(path)
+            self._path = os.path.basename(path)
+        else:
+            self._base_dir = base_dir
+            self._path = path
+
         self._offset: int | None = offset
         self._length: int | None = length
         self._dtype: _enums.DataType = dtype
@@ -528,6 +537,15 @@ def path(self) -> str | os.PathLike:
         # Immutable
         return self._path
 
+    @property
+    def base_dir(self) -> str | os.PathLike:
+        # Mutable
+        return self._base_dir
+
+    @base_dir.setter
+    def base_dir(self, value: str | os.PathLike) -> None:
+        self._base_dir = value
+
     @property
     def offset(self) -> int | None:
         # Immutable
@@ -556,7 +574,8 @@ def _load(self):
             return
         # Map the whole file into the memory
         # TODO(justinchuby): Verify if this would exhaust the memory address space
-        with open(self._path, "rb") as f:
+        file_path = os.path.join(self._base_dir, self._path)
+        with open(file_path, "rb") as f:
             self.raw = mmap.mmap(
                 f.fileno(),
                 0,
@@ -599,7 +618,10 @@ def __dlpack_device__(self) -> tuple[int, int]:
         )
 
     def __repr__(self) -> str:
-        return f"{self._repr_base()}(path='{self._path}', name={self.name!r}, offset={self._offset!r}), length={self._length!r})"
+        return (
+            f"{self._repr_base()}(path='{self._path}', name={self.name!r}, "
+            f"offset={self._offset!r}, length={self._length!r}, base_dir={self._base_dir!r})"
+        )
 
     def numpy(self) -> np.ndarray:
         """Return the tensor as a numpy array.
@@ -2069,7 +2091,7 @@ def __init__(
         outputs: Sequence[Value],
         *,
         nodes: Iterable[Node],
-        initializers: Sequence[_protocols.TensorProtocol] = (),
+        initializers: Sequence[_protocols.ValueProtocol] = (),
         doc_string: str | None = None,
         opset_imports: dict[str, int] | None = None,
         name: str | None = None,
diff --git a/onnxscript/ir/_core_test.py b/onnxscript/ir/_core_test.py
index 1fbbca692..c284fa365 100644
--- a/onnxscript/ir/_core_test.py
+++ b/onnxscript/ir/_core_test.py
@@ -243,6 +243,23 @@ def test_initialize(self):
         # Ensure repeated reads are consistent
         np.testing.assert_equal(tensor, self.data)
 
+    def test_initialize_with_relative_path(self):
+        external_tensor = self.model.graph.initializer[0]
+        external_info = onnx.external_data_helper.ExternalDataInfo(external_tensor)
+        tensor = _core.ExternalTensor(
+            path=external_info.location,
+            offset=external_info.offset,
+            length=external_info.length,
+            dtype=ir.DataType.FLOAT,
+            name="input",
+            shape=_core.Shape(external_tensor.dims),
+            base_dir=pathlib.Path(self.base_path),
+        )
+        self.assertEqual(tensor.dtype, ir.DataType.FLOAT)
+        np.testing.assert_equal(tensor, self.data)
+        # Ensure repeated reads are consistent
+        np.testing.assert_equal(tensor, self.data)
+
     def test_totypes_returns_correct_data_in(self):
         external_tensor = self.model.graph.initializer[0]
         external_info = onnx.external_data_helper.ExternalDataInfo(external_tensor)
diff --git a/onnxscript/ir/_external_data.py b/onnxscript/ir/_external_data.py
new file mode 100644
index 000000000..3d19bae5c
--- /dev/null
+++ b/onnxscript/ir/_external_data.py
@@ -0,0 +1,53 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+"""External data related utilities."""
+
+from __future__ import annotations
+
+__all__ = ["set_base_dir"]
+
+import os
+from typing import Iterator
+
+from onnxscript.ir import _core, _enums, _protocols, traversal
+
+
+def _all_tensors(
+    graph: _core.Graph | _core.GraphView, include_attributes: bool = False
+) -> Iterator[_protocols.TensorProtocol]:
+    """Iterate over all tensors in the graph.
+
+    Args:
+        graph: The graph to traverse tensors on.
+        include_attributes: Whether to include tensors in attributes.
+
+    Yields:
+        Tensors in the graph.
+    """
+    # Yield all tensors in initializers
+    for value in graph.initializers.values():
+        if value.const_value is not None:
+            yield value.const_value
+    if not include_attributes:
+        return
+    # Look at constant attributes in nodes
+    for node in traversal.RecursiveGraphIterator(graph):
+        for attr in node.attributes.values():
+            if isinstance(attr, _core.RefAttr):
+                continue
+            if attr.type == _enums.AttributeType.TENSOR and attr.value is not None:
+                yield attr.value
+            elif attr.type == _enums.AttributeType.TENSORS and attr.value is not None:
+                yield from attr.value
+
+
+def set_base_dir(graph: _core.Graph | _core.GraphView, base_dir: str | os.PathLike) -> None:
+    """Set the base directory for external data in a graph.
+
+    Args:
+        graph: The graph to traverse tensors on.
+        base_dir: The base directory. This is the directory where the ONNX file is.
+    """
+    for tensor in _all_tensors(graph, include_attributes=True):
+        if isinstance(tensor, _core.ExternalTensor):
+            tensor.base_dir = base_dir
diff --git a/onnxscript/ir/_external_data_test.py b/onnxscript/ir/_external_data_test.py
new file mode 100644
index 000000000..624f7e0a5
--- /dev/null
+++ b/onnxscript/ir/_external_data_test.py
@@ -0,0 +1,59 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+import unittest
+
+import onnx
+import onnx.external_data_helper
+
+from onnxscript import ir
+from onnxscript.ir import _external_data
+
+
+class ExternalDataTest(unittest.TestCase):
+    def test_set_base_dir_sets_base_dir_for_all_external_tensors(self):
+        attr_tensor = onnx.helper.make_tensor(
+            name="test_constant",
+            data_type=onnx.TensorProto.FLOAT,
+            dims=[1],
+            vals=b"\x01\x00\x00\x00",
+            raw=True,
+        )
+        graph = onnx.helper.make_graph(
+            nodes=[
+                onnx.helper.make_node(
+                    "Constant",
+                    [],
+                    ["test"],
+                    value=attr_tensor,
+                )
+            ],
+            name="test",
+            inputs=[],
+            outputs=[],
+            initializer=[
+                onnx.helper.make_tensor(
+                    name="test_tensor",
+                    data_type=onnx.TensorProto.FLOAT,
+                    dims=[1],
+                    vals=b"\x01\x00\x00\x00",
+                    raw=True,
+                ),
+            ],
+        )
+        model_proto = onnx.helper.make_model(graph)
+        onnx.external_data_helper.convert_model_to_external_data(
+            model_proto, location="tempdir", size_threshold=0, convert_attribute=True
+        )
+        model = ir.serde.deserialize_model(model_proto)
+        expected_dir = "something_else"
+        _external_data.set_base_dir(model.graph, expected_dir)
+
+        initializer_tensor = model.graph.initializers["test_tensor"].const_value
+        assert isinstance(initializer_tensor, ir.ExternalTensor)
+        self.assertEqual(initializer_tensor.base_dir, expected_dir)
+        attr_tensor = model.graph.node(0).attributes["value"].value
+        self.assertEqual(attr_tensor.base_dir, expected_dir)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/onnxscript/ir/_io.py b/onnxscript/ir/_io.py
new file mode 100644
index 000000000..a9c867f3f
--- /dev/null
+++ b/onnxscript/ir/_io.py
@@ -0,0 +1,50 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+"""Load and save ONNX models."""
+
+from __future__ import annotations
+
+__all__ = ["load", "save"]
+
+import os
+
+import onnx
+
+from onnxscript.ir import _core, _external_data, serde
+
+
+def load(path: str | os.PathLike, format: str | None = None) -> _core.Model:
+    """Load an ONNX model from a file.
+
+    Args:
+        path: The path to the ONNX file.
+        format: The format of the file (e.g. protobuf, textproto, json, etc.).
+            If None, the format is inferred from the file extension.
+
+    Returns:
+        The loaded model.
+    """
+    # Do not use ONNX to load external data because the IR handles external data
+    # by doing memory mapping directly.
+    proto = onnx.load(path, format=format, load_external_data=False)
+    model = serde.deserialize_model(proto)
+    base_dir = os.path.dirname(path)
+    # Set the base directory for external data to the directory of the ONNX file
+    # so that relative paths are resolved correctly.
+    _external_data.set_base_dir(model.graph, base_dir)
+    return model
+
+
+def save(model: _core.Model, path: str | os.PathLike, format: str | None = None) -> None:
+    """Save an ONNX model to a file.
+
+    Args:
+        model: The model to save.
+        path: The path to save the model to.
+        format: The format of the file (e.g. protobuf, textproto, json, etc.).
+            If None, the format is inferred from the file extension.
+    """
+    proto = serde.serialize_model(model)
+    onnx.save(proto, path, format=format)
+    # TODO(justinchuby): Handle external data when the relative path has changed
+    # TODO(justinchuby): Handle off loading external data to disk when saving
diff --git a/onnxscript/ir/traversal.py b/onnxscript/ir/traversal.py
index 5951506fe..5fa9a9acf 100644
--- a/onnxscript/ir/traversal.py
+++ b/onnxscript/ir/traversal.py
@@ -8,17 +8,19 @@
     "RecursiveGraphIterator",
 ]
 
-from typing import Callable, Iterator, Reversible
+from typing import Callable, Iterator, Reversible, Union
 
 from typing_extensions import Self
 
 from onnxscript.ir import _core, _enums
 
+GraphLike = Union[_core.Graph, _core.Function, _core.GraphView]
+
 
 class RecursiveGraphIterator(Iterator[_core.Node], Reversible[_core.Node]):
     def __init__(
         self,
-        graph: _core.Graph | _core.Function | _core.GraphView,
+        graph_like: GraphLike,
         *,
         recursive: Callable[[_core.Node], bool] | None = None,
         reverse: bool = False,
@@ -26,15 +28,15 @@ def __init__(
         """Iterate over the nodes in the graph, recursively visiting subgraphs.
 
         Args:
-            graph: The graph to traverse.
+            graph_like: The graph to traverse.
             recursive: A callback that determines whether to recursively visit the subgraphs
                 contained in a node. If not provided, all nodes in subgraphs are visited.
             reverse: Whether to iterate in reverse order.
         """
-        self._graph = graph
+        self._graph = graph_like
         self._recursive = recursive
         self._reverse = reverse
-        self._iterator = self._recursive_node_iter(graph)
+        self._iterator = self._recursive_node_iter(graph_like)
 
     def __iter__(self) -> Self:
         self._iterator = self._recursive_node_iter(self._graph)