[AutoRound] Support WAN2.2 W4A16 quantization model (#3353)
Signed-off-by: lvliang-intel <liang1.lv@intel.com> Signed-off-by: hyh_hh <huyinghong1@huawei.com> Co-authored-by: hxhhhlalala <hyh_hh@163.com> Co-authored-by: hyh_hh <huyinghong1@huawei.com>
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@@ -32,7 +32,9 @@ guide. AutoRound is Intel-supported.
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|-------|------------|-------|--------|---------|
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| FLUX.1-dev | `vllm-project-org/FLUX.1-dev-AutoRound-w4a16` | Diffusion transformer | W4A16 | GPTQ-Marlin or Intel-supported AutoRound backend |
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| Qwen-Image | Not listed | Diffusion transformer | W4A16 | Not validated |
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| Wan2.2 | Not listed | Diffusion transformer | W4A16 | Not validated |
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| Wan2.2-I2V | `Intel/Wan2.2-I2V-A14B-Diffusers-int4-AutoRound` | Diffusion transformer | W4A16 | GPTQ-Marlin or Intel-supported AutoRound backend |
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| Wan2.2-T2V | `Intel/Wan2.2-T2V-A14B-Diffusers-int4-AutoRound` | Diffusion transformer | W4A16 | GPTQ-Marlin or Intel-supported AutoRound backend |
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| Wan2.2-TI2V | `Intel/Wan2.2-TI2V-5B-Diffusers-int4-AutoRound` | Diffusion transformer | W4A16 | GPTQ-Marlin or Intel-supported AutoRound backend |
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### Multi-Stage Omni/TTS Model (Qwen3-Omni, Qwen3-TTS)
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@@ -397,7 +397,7 @@ names** discovered in Step 1. No code changes to the model are required.
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```python
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omni = Omni(
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model="/path/to/your-model",
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quantization_config={
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quantization={
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"method": "mxfp4_dualscale",
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"ignored_layers": [
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"blocks.0.attn1.to_qkv", # runtime name, not diffusers name
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