docs: qualify SALM Automodel parallelism support

docs/source/speechlm2/training_and_scaling.rst

@@ -101,8 +101,10 @@ AutomodelParallelStrategy (SALMAutomodel)
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 For ``SALMAutomodel``, the collection provides ``AutomodelParallelStrategy`` which
-delegates device mesh creation and parallelism to NeMo Automodel. This strategy
-supports FSDP2, TP, PP, CP, EP (MoE), and HSDP.
+delegates device mesh creation and parallelism to NeMo Automodel. The strategy can
+construct device meshes for FSDP2, TP, PP, CP, EP (MoE), and HSDP, but actual
+support depends on the selected LLM architecture, backend, and combination of
+parallelism axes.
 
 .. code-block:: yaml
 
@@ -165,6 +167,16 @@ optimizations:
   primitive for routing tokens to experts across GPUs, significantly reducing the
   communication overhead of Expert Parallelism.
 
+.. important::
+   For the native Nemotron-V3 backbone, the validated ``SALMAutomodel``
+   parallelism axes are FSDP2, EP, and CP. CP requires packed sequences and
+   Transformer Engine attention, as described in the Context Parallelism
+   section below.
+
+   Nemotron-V3 does not provide a TP plan, so set ``tp_size: 1``. HSDP is not
+   supported in this path, so set ``dp_replicate_size: 1``. PP has not been
+   validated for this SpeechLM2 configuration, so set ``pp_size: 1``.
+
 Example: training SALMAutomodel with Nemotron Nano V3 on 8 GPUs with EP=8:
 
 .. code-block:: bash