diff --git a/src/maxtext/layers/attention_op.py b/src/maxtext/layers/attention_op.py
index d265459e69..ee91098623 100644
--- a/src/maxtext/layers/attention_op.py
+++ b/src/maxtext/layers/attention_op.py
@@ -1570,10 +1570,14 @@ def cudnn_flash_attention(
       qkv_layout = "THD_THD_THD"  # Packed format: 'T3HD', 'THD_T2HD' or 'THD_THD_THD'
       if decoder_segment_ids is None:
         decoder_segment_ids = jnp.ones(shape=query.shape[:2], dtype=jnp.int32)
-      attn_mask = SequenceDescriptor.from_segment_ids_and_pos(segment_ids=decoder_segment_ids, segment_pos=None)
+      attn_mask = SequenceDescriptor.from_segment_ids_and_pos(
+          segment_ids=decoder_segment_ids, segment_pos=None, is_thd=True, is_segment_ids_reordered=False
+      )
       # Create dummy SequenceDescriptor for lazy_init
       dummy_segment_ids = jnp.ones(shape=query.shape[:2], dtype=jnp.int32)
-      dummy_attn_mask = SequenceDescriptor.from_segment_ids_and_pos(segment_ids=dummy_segment_ids, segment_pos=None)
+      dummy_attn_mask = SequenceDescriptor.from_segment_ids_and_pos(
+          segment_ids=dummy_segment_ids, segment_pos=None, is_thd=True, is_segment_ids_reordered=False
+      )
       max_segments_per_seq = self.config.max_segments_per_seq
     elif using_context_parallelism:
       if self.attention_type == AttentionType.LOCAL_SLIDING:
diff --git a/tests/integration/train_tests.py b/tests/integration/train_tests.py
index cc55f07844..5c81f059cb 100644
--- a/tests/integration/train_tests.py
+++ b/tests/integration/train_tests.py
@@ -582,6 +582,45 @@ def test_gpu_packed_attention(self):
     ]
     train_main(packed_attention)
 
+  @pytest.mark.integration_test
+  @pytest.mark.gpu_only
+  def test_gpu_packed_attention_hf(self):
+    """Packed (THD) cuDNN TE attention with real HF data.
+
+    Unlike test_gpu_packed_attention (which uses synthetic data and bypasses
+    SequenceDescriptor), this test exercises the SequenceDescriptor.from_segment_ids_and_pos()
+    codepath that is only reached when packing=True AND dataset_type != 'synthetic'.
+    Regression test for NVIDIA/TransformerEngine#2523.
+    """
+    gpu_device = jax.devices("gpu")[0]
+    compute_capability = getattr(gpu_device, "compute_capability", None)
+    try:
+      if float(compute_capability) < 9.0:
+        pytest.skip("Packed (THD) attention is only supported on sm90+!")
+    except Exception:  # pylint: disable=broad-exception-caught
+      print("checking if Packed THD attention is supported on this host...")
+      pytest.skip("Packed (THD) attention is only supported on sm90+!")
+    os.environ["NVTE_FUSED_ATTN"] = "1"
+    packed_attention_hf = [
+        None,
+        get_test_config_path(),
+        f"base_output_directory={self._base_output_directory}",
+        "run_name=runner_test",
+        f"dataset_path={self.dataset_path}",
+        "dataset_type=hf",
+        "hf_path=parquet",
+        f"hf_train_files={self.dataset_path}/hf/c4/c4-train-00000-of-01637.parquet",
+        "tokenizer_path=google-t5/t5-large",
+        "steps=2",
+        "enable_checkpointing=False",
+        "enable_goodput_recording=False",
+        "attention=cudnn_flash_te",
+        "ici_fsdp_parallelism=-1",
+        "packing=True",
+        "max_segments_per_seq=32",
+    ]
+    train_main(packed_attention_hf)
+
   @pytest.mark.integration_test
   @pytest.mark.gpu_only
   @pytest.mark.skip(reason="b/489133823. Previously transient in b/462548581.")