[NPU] [Quant] Support HunyuanImage3 offline quantization with vLLM-Ascend on diffusion path (#2979)

Signed-off-by: betta18 <jiangmengyu1@huawei.com>
Signed-off-by: jiangmengyu18 <56633611+jiangmengyu18@users.noreply.github.com>
Co-authored-by: betta18 <jiangmengyu1@huawei.com>

docs/user_guide/diffusion/quantization/msmodelslim.md

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+# msModelSlim Quantization
+
+## Overview
+
+[msModelSlim](https://github.com/Ascend/msmodelslim) is an Ascend-friendly compression tool focused on acceleration, using compression techniques, and built for Ascend hardware. It includes a series of inference optimization technologies such as quantization and compression, aiming to accelerate large language dense models, MoE models, multimodal understanding models, multimodal generation models, etc.
+
+Once you have a quantized model which is generated by **msModelSlim**, you can use vLLM Omni for inference by specifying the --quantization ascend parameter to enable quantization features.
+
+### Supported Schemes
+
+| Scheme | Bits | Status |
+|--------|------|--------|
+| W8A8 | 8 | ✅ Supported |
+| W4A4 | 4 | Planned |
+
+W8A8 is the first supported scheme. Additional schemes will be added in future releases.
+
+## Model Quantization
+
+The following example shows how to generate W8A8 quantized weights for the [Wan2_2 model](https://gitcode.com/Ascend/msmodelslim/blob/master/example/multimodal_sd/Wan2_2/README.md).
+
+**Quantization Script:**
+
+```bash
+msmodelslim quant \
+  --model_path /path/to/wan2_2_t2v_float_weights \
+  --save_path /path/to/wan2_2_t2v_quantized_weights \
+  --device npu \
+  --model_type Wan2_2 \
+  --config_path /lab_practice/wan2_2/wan2_2_w8a8f8_mxfp_t2v.yaml \
+  --trust_remote_code True
+```
+
+After quantization completes, the output directory will contain the quantized model files.
+
+For more examples, refer to the [official examples](https://gitcode.com/Ascend/msit/tree/master/msmodelslim/example).
+
+## Configuration
+
+1. **CLI**: pass `--quantization ascend`.
+
+```bash
+# Offline inference
+python text_to_image.py --model <your-model> --quantization ascend
+
+# Online serving
+vllm serve <your-model> --omni --quantization ascend
+```
+
+## Supported Models
+
+| Model | HF Models | Recommendation | `ignored_layers` |
+|-------|-----------|---------------|------------------|
+| HunyuanImage-3.0 | - | All layers | None |
+
+Currently, quantized HunyuanImage-3.0 weights have not been uploaded to public model platforms such as Hugging Face. You can use a [HunyuanImage-3.0-adapted msModelSlim version](https://gitcode.com/betta18/msmodelslim/tree/hyimage3_mxfp8) to generate the quantized weights manually. We will upload the quantized weights as soon as possible.