diff --git a/torchtune/modules/low_precision/_register_nf4_dispatch_ops.py b/torchtune/modules/low_precision/_register_nf4_dispatch_ops.py
index b057a1fbc3..037891ac36 100644
--- a/torchtune/modules/low_precision/_register_nf4_dispatch_ops.py
+++ b/torchtune/modules/low_precision/_register_nf4_dispatch_ops.py
@@ -6,7 +6,6 @@
 
 import torch
 from torchao.dtypes.nf4tensor import implements as nf4_tensor_impl, to_nf4
-from torchtune.modules.low_precision._utils import _get_torchao_version
 
 
 @nf4_tensor_impl([torch.ops.aten.clone.default])
@@ -18,37 +17,3 @@ def clone(func, *args, **kwargs):
     in precision.
     """
     return to_nf4(args[0][0].get_original_weight())
-
-
-should_define_inplace_copy = True
-ao_version, is_nightly = _get_torchao_version()
-if ao_version:
-    if (is_nightly and ao_version >= "2024.5.20") or (
-        not is_nightly and ao_version >= "0.2.0"
-    ):
-        should_define_inplace_copy = False
-
-if should_define_inplace_copy:
-    # TorchAO have `NF4.copy_` starting from `0.2.0`
-    # it's a superset of `inplace_copy` since it covers `NF4.copy_(NF4)`
-    @nf4_tensor_impl([torch.ops.aten.copy_.default])
-    def inplace_copy(func, *args, **kwargs):
-        """
-        Performs an inplace copy of an incoming tensor into the tensor
-        being copied into. The inplace tensor is given by args[0][1] and the
-        tensor being copied into is given by args[0][0]. The copy is performed
-        by copying over all attributes. This method would have to be updated
-        if additional attributes are added to NF4Tensor.
-        """
-        dest_tensor = args[0][0]  # tensor we are inplace copying into
-        ref_tensor = to_nf4(
-            args[0][1].to(dest_tensor.device)
-        )  # TODO check if nf4 tensor takes in device arg
-        dest_tensor.block_size = ref_tensor.block_size
-        dest_tensor.n_blocks = ref_tensor.n_blocks
-        dest_tensor.scaler_block_size = ref_tensor.scaler_block_size
-        dest_tensor.quantized_scalers = ref_tensor.quantized_scalers
-        dest_tensor.quantization_factor = ref_tensor.quantization_factor
-        dest_tensor.scaler_mean = ref_tensor.scaler_mean
-        dest_tensor.quantized_data = ref_tensor.quantized_data
-        dest_tensor.nf4 = ref_tensor.nf4