diff --git a/axlearn/experiments/text/gpt/fuji.py b/axlearn/experiments/text/gpt/fuji.py
index cc6ecdf56..5bbfff261 100644
--- a/axlearn/experiments/text/gpt/fuji.py
+++ b/axlearn/experiments/text/gpt/fuji.py
@@ -176,12 +176,10 @@ def get_trainer_kwargs(
                 rope_theta=rope_theta,
                 shared_lm_head=True,
                 flash_attention=flash_attention,
-                stack_cfg=None if backend != "neuron" else StackedTransformerLayer.default_config(),
             ),
             learner_kwargs=dict(peak_lr=3e-4, weight_decay=0.1),
             max_sequence_length=max_sequence_length,
             train_batch_size=train_batch_size,
-            input_partition_type=None if backend != "neuron" else DataPartitionType.BATCH,
             max_step=max_step,
             mesh_shape=mesh_shape_from_axes(data=-1, fsdp=8),
             mesh_rules=(
@@ -202,12 +200,10 @@ def get_trainer_kwargs(
                 rope_theta=rope_theta,
                 shared_lm_head=True,
                 flash_attention=flash_attention,
-                stack_cfg=None if backend != "neuron" else StackedTransformerLayer.default_config(),
             ),
             learner_kwargs=dict(peak_lr=3e-4, weight_decay=0.1),
             max_sequence_length=max_sequence_length,
             train_batch_size=train_batch_size,
-            input_partition_type=None if backend != "neuron" else DataPartitionType.BATCH,
             max_step=max_step,
             mesh_shape=mesh_shape_from_axes(data=-1, fsdp=8),
             mesh_rules=(
@@ -227,12 +223,10 @@ def get_trainer_kwargs(
                 rope_theta=rope_theta,
                 shared_lm_head=True,
                 flash_attention=flash_attention,
-                stack_cfg=None if backend != "neuron" else StackedTransformerLayer.default_config(),
             ),
             learner_kwargs=dict(peak_lr=3e-4, weight_decay=0.1),
             max_sequence_length=max_sequence_length,
             train_batch_size=train_batch_size,
-            input_partition_type=None if backend != "neuron" else DataPartitionType.BATCH,
             max_step=max_step,
             mesh_shape=mesh_shape_from_axes(data=-1, fsdp=8),
             mesh_rules=(
@@ -334,12 +328,10 @@ def get_trainer_kwargs(
                 rope_theta=rope_theta,
                 shared_lm_head=False,
                 flash_attention=flash_attention,
-                stack_cfg=None if backend != "neuron" else StackedTransformerLayer.default_config(),
             ),
             learner_kwargs=dict(peak_lr=3e-4, weight_decay=0.1),
             max_sequence_length=max_sequence_length,
             train_batch_size=train_batch_size,
-            input_partition_type=None if backend != "neuron" else DataPartitionType.BATCH,
             max_step=max_step,
             mesh_shape=mesh_shape_from_axes(data=-1, fsdp=8),
             mesh_rules=(
@@ -426,7 +418,6 @@ def get_trainer_kwargs(
             learner_kwargs=dict(peak_lr=1.5e-4, weight_decay=0.1),
             max_sequence_length=max_sequence_length,
             train_batch_size=train_batch_size,
-            input_partition_type=None if backend != "neuron" else DataPartitionType.BATCH,
             max_step=max_step,
             mesh_shape=mesh_shape_from_axes(fsdp=-1),
             mesh_rules=(
@@ -474,6 +465,7 @@ def get_trainer_kwargs(
         max_step=trainer_kwargs["max_step"],
         **trainer_kwargs.pop("learner_kwargs"),
     )
+    trainer_kwargs.setdefault("input_partition_type", None if backend != "neuron" else DataPartitionType.BATCH)
     # pylint: enable=use-dict-literal
     return trainer_kwargs