Force torch>=2.6 with torch.load to avoid vulnerability issue (#37785)

* fix all main files

* fix test files

* oups forgot modular

* add link

* update message

src/transformers/modeling_utils.py

@@ -94,6 +94,7 @@ from .utils import (
     ModelOutput,
     PushToHubMixin,
     cached_file,
+    check_torch_load_is_safe,
     copy_func,
     download_url,
     extract_commit_hash,
@@ -445,7 +446,11 @@ def load_sharded_checkpoint(model, folder, strict=True, prefer_safe=True):
             error_message += f"\nMissing key(s): {str_unexpected_keys}."
         raise RuntimeError(error_message)
 
-    loader = safe_load_file if load_safe else partial(torch.load, map_location="cpu", weights_only=True)
+    if load_safe:
+        loader = safe_load_file
+    else:
+        check_torch_load_is_safe()
+        loader = partial(torch.load, map_location="cpu", weights_only=True)
 
     for shard_file in shard_files:
         state_dict = loader(os.path.join(folder, shard_file))
@@ -490,6 +495,7 @@ def load_state_dict(
     """
     Reads a `safetensor` or a `.bin` checkpoint file. We load the checkpoint on "cpu" by default.
     """
+    # Use safetensors if possible
     if checkpoint_file.endswith(".safetensors") and is_safetensors_available():
         with safe_open(checkpoint_file, framework="pt") as f:
             metadata = f.metadata()
@@ -512,6 +518,9 @@ def load_state_dict(
                     state_dict[k] = f.get_tensor(k)
             return state_dict
 
+    # Fallback to torch.load (if weights_only was explicitly False, do not check safety as this is known to be unsafe)
+    if weights_only:
+        check_torch_load_is_safe()
     try:
         if map_location is None:
             if (