Add ModelOpt NVFP4 pipeline: patch, run script, README

- Patch fixes iter_weights_for_calibration() for DeepseekV4Experts
  (ModuleList quantizers vs singular)
- Run script uses official NVIDIA hf_ptq.py with FP8 source
- Documents flags to avoid (--low_memory_mode, wrong arg names)

scripts/run_modelopt_nvfp4.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+# DeepSeek V4 Pro FP8 → NVFP4 via NVIDIA ModelOpt
+# Run from: /root/nvidia-meeting/modelopt-repo/examples/llm_ptq
+#
+# Prerequisites:
+#   - modelopt 0.45.0+ from git: pip install "nvidia-modelopt[hf] @ git+https://github.com/NVIDIA/Model-Optimizer.git"
+#   - transformers 5.8.0.dev0: pip install git+https://github.com/huggingface/transformers.git
+#   - kernels: pip install -U kernels
+#   - Patch modelopt: cp patches/quant_module_patched.py <venv>/lib/python3.10/site-packages/modelopt/torch/quantization/nn/modules/quant_module.py
+#
+# Source weights: /root/nvidia-meeting/DeepSeek-V4-Pro-FP8
+
+set -e
+cd /root/nvidia-meeting/modelopt-repo/examples/llm_ptq
+source /root/nvidia-meeting/venv/bin/activate
+
+PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
+bash scripts/huggingface_example.sh \
+    --model /root/nvidia-meeting/DeepSeek-V4-Pro-FP8 \
+    --quant nvfp4 \
+    --tp 8 \
+    --calib 256 \
+    --kv_cache_quant fp8_cast \
+    --trust_remote_code \
+    --use_seq_device_map