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update README
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multimodal/qwen3-vl/README.md

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@@ -300,9 +300,14 @@ mlperf-inf-mm-q3vl-foo/
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└── src/
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└── mlperf_inf_mm_q3vl_foo/
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├── __init__.py
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├── schema.py
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├── deploy.py
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└── plugin.py
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```
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Note that this is only a minimalistically illustrative example. The users are free to
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structure and name their Python packages and modules in any way that they wish.
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#### Step 2: Implement the `mlperf-inf-mm-q3vl-foo` plugin
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Create your plugin entry point function in `plugin.py`:
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from .schema import FooEndpoint
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def register_foo_benchmark() -> Callable[[Settings, Dataset, FooEndpoint, int, int, Verbosity], None]:
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def register_foo_benchmark() -> Callable:
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"""Entry point for the plugin to benchmark the Foo inference system.
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This function is called when the CLI discovers the plugin.

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