Revert low cpu mem tie weights (#29135)

* Revert "Add tie_weights() to LM heads and set bias in set_output_embeddings() (#28948)"

This reverts commit 725f4ad1cc.

* Revert "Patch to skip failing `test_save_load_low_cpu_mem_usage` tests (#29043)"

This reverts commit 4156f517ce.

tests/test_modeling_common.py

@@ -435,23 +435,6 @@ class ModelTesterMixin:
                         max_diff = (model_slow_init.state_dict()[key] - model_fast_init.state_dict()[key]).sum().item()
                     self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
 
-    def test_save_load_low_cpu_mem_usage(self):
-        with tempfile.TemporaryDirectory() as tmpdirname:
-            for model_class in self.all_model_classes:
-                config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
-                model_to_save = model_class(config)
-
-                model_to_save.save_pretrained(tmpdirname)
-
-                model = model_class.from_pretrained(
-                    tmpdirname,
-                    low_cpu_mem_usage=True,
-                )
-
-                # The low_cpu_mem_usage=True causes the model params to be initialized with device=meta. If there are
-                # any unloaded or untied parameters, then trying to move it to device=torch_device will throw an error.
-                model.to(torch_device)
-
     def test_fast_init_context_manager(self):
         # 1. Create a dummy class. Should have buffers as well? To make sure we test __init__
         class MyClass(PreTrainedModel):