Move the QLoRA export changelog entry to 0.46

The PR is labeled cherry-pick-0.46.0, so the entry belongs in the 0.46 section.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Signed-off-by: Suguna Velury <178320438+sugunav14@users.noreply.github.com>

Author: sugunav14

CHANGELOG.rst

@@ -21,8 +21,6 @@ Changelog
 
 **Bug Fixes**
 
-- Fix QLoRA export in ``examples/llm_qat/export.py`` failing with ``AssertionError: Model already has modelopt state!`` (NVBug 6542481). The QLoRA training output is an adapter-only checkpoint, so ``from_pretrained`` resolves the quantized base model from ``adapter_config.json`` and ``enable_huggingface_checkpointing`` already restores its ModelOpt state; the export then restored a second time. It now restores only when the loaded model is not already converted. Two further breakages on the same path are also fixed: ``_restore_qtensor_wrappers`` matched no modules because PEFT re-parents the quantized linear as ``<name>.base_layer`` while ``q_tensor_state`` is keyed by the name it was saved with (the packed NVFP4 weight then reached ``F.linear`` and raised a shape error), and ``postprocess_state_dict`` silently dropped every ``base_layer.*`` key missing from a hand-maintained rename map — losing the NVFP4 ``weight_scale_2`` global scale and any linear ``bias`` (Qwen2-style q/k/v biases), and leaving ``base_layer`` in the exported AWQ ``pre_quant_scale`` key. The rename is now a generic ``.base_layer.`` strip.
-
 0.46 (2026-08-xx)
 ^^^^^^^^^^^^^^^^^
 
@@ -104,6 +102,7 @@ Changelog
 - Fix ``examples/vllm_serve`` serving shared experts uncalibrated: their ``gate_proj``/``up_proj`` quantizer keys were not merged into ``gate_up_proj`` on reload, so they matched no module and were dropped.
 - Fix Qwen3-VL MoE PTQ failing on ``transformers>=5.12`` with ``AttributeError: 'QuantQwen3VLMoeTextExperts' object has no attribute 'hidden_size'`` (NVBug 6518551). transformers 5.12 moved ``Qwen3VLMoeTextExperts`` onto the standard ``@use_experts_implementation`` fused layout (``hidden_size``/``expert_dim`` renamed to ``hidden_dim``/``intermediate_dim``, ``gate_up_proj`` transposed to ``(num_experts, 2*intermediate_dim, hidden_dim)``, two ``F.linear`` calls per expert), but the legacy ``_QuantQwen3VLMoeTextExperts`` wrapper stayed statically registered and shadowed on-the-fly detection. The new layout is now left to ``register_fused_experts_on_the_fly``, which claims it with the generic ``_QuantFusedExperts``; the legacy wrapper is still registered on ``transformers<5.12``, whose ``torch.bmm``-based forward the generic wrapper cannot intercept.
 - Fix ``examples/hf_ptq`` multi-node FSDP2 export (``--use_fsdp2``) failing with ``RuntimeError: Cannot set version_counter for inference tensor``. ``export_quantized`` wrapped its whole body in ``torch.inference_mode()``, so the full params gathered by ``get_model_state_dict(full_state_dict=True)`` were inference tensors and the subsequent ``state_dict()`` -> ``param.detach()`` could not set their version counter. The export context is now ``torch.no_grad()``, which still disables autograd but keeps the gathered params as normal tensors.
+- Fix QLoRA export in ``examples/llm_qat/export.py`` failing with ``AssertionError: Model already has modelopt state!`` (NVBug 6542481). The QLoRA training output is an adapter-only checkpoint, so ``from_pretrained`` resolves the quantized base model from ``adapter_config.json`` and ``enable_huggingface_checkpointing`` already restores its ModelOpt state; the export then restored a second time. It now restores only when the loaded model is not already converted. Two further breakages on the same path are also fixed: ``_restore_qtensor_wrappers`` matched no modules because PEFT re-parents the quantized linear as ``<name>.base_layer`` while ``q_tensor_state`` is keyed by the name it was saved with (the packed NVFP4 weight then reached ``F.linear`` and raised a shape error), and ``postprocess_state_dict`` silently dropped every ``base_layer.*`` key missing from a hand-maintained rename map — losing the NVFP4 ``weight_scale_2`` global scale and any linear ``bias`` (Qwen2-style q/k/v biases), and leaving ``base_layer`` in the exported AWQ ``pre_quant_scale`` key. The rename is now a generic ``.base_layer.`` strip.
 
 0.45 (2026-07-02)
 ^^^^^^^^^^^^^^^^^