remove context manager when loading shards and handle mlx weights (#2709

)

src/huggingface_hub/serialization/_torch.py

@@ -18,10 +18,9 @@
 import os
 import re
 from collections import defaultdict, namedtuple
-from contextlib import contextmanager
 from functools import lru_cache
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, NamedTuple, Optional, Set, Tuple, Union
+from typing import TYPE_CHECKING, Any, Dict, Iterable, List, NamedTuple, Optional, Set, Tuple, Union
 
 from packaging import version
 
@@ -538,13 +537,15 @@ def _load_sharded_checkpoint(
     for shard_file in shard_files:
         # Load shard into memory
         shard_path = os.path.join(save_directory, shard_file)
-        with _load_shard_into_memory(
+        state_dict = load_state_dict_from_file(
             shard_path,
-            load_fn=load_state_dict_from_file,
-            kwargs={"weights_only": weights_only},
-        ) as state_dict:
-            # Update model with parameters from this shard
-            model.load_state_dict(state_dict, strict=strict)
+            map_location="cpu",
+            weights_only=weights_only,
+        )
+        # Update model with parameters from this shard
+        model.load_state_dict(state_dict, strict=strict)
+        # Explicitly remove the state dict from memory
+        del state_dict
 
     # 4. Return compatibility info
     loaded_keys = set(index["weight_map"].keys())
@@ -630,7 +631,8 @@ def load_state_dict_from_file(
         # Check format of the archive
         with safe_open(checkpoint_file, framework="pt") as f:  # type: ignore[attr-defined]
             metadata = f.metadata()
-        if metadata.get("format") != "pt":
+        # see comment: https://github.com/huggingface/transformers/blob/3d213b57fe74302e5902d68ed9478c3ad1aaa713/src/transformers/modeling_utils.py#L3966
+        if metadata is not None and metadata.get("format") not in ["pt", "mlx"]:
             raise OSError(
                 f"The safetensors archive passed at {checkpoint_file} does not contain the valid metadata. Make sure "
                 "you save your model with the `save_torch_model` method."
@@ -668,30 +670,6 @@ def load_state_dict_from_file(
 # HELPERS
 
 
-@contextmanager
-def _load_shard_into_memory(
-    shard_path: str,
-    load_fn: Callable,
-    kwargs: Optional[Dict[str, Any]] = None,
-):
-    """
-    Context manager to handle loading and cleanup of model shards.
-
-    Args:
-        shard_path: Path to the shard file
-        load_fn: Function to load the shard (either torch.load or safetensors.load)
-
-    Yields:
-        The loaded state dict for this shard
-    """
-    try:
-        state_dict = load_fn(shard_path, **kwargs)  # type: ignore[arg-type]
-        yield state_dict
-    finally:
-        # Explicitly remove the state dict from memory
-        del state_dict
-
-
 def _validate_keys_for_strict_loading(
     model: "torch.nn.Module",
     loaded_keys: Iterable[str],