[Doc][Misc] Comprehensive documentation cleanup and grammatical fixes (#8073)
What this PR does / why we need it? This pull request performs a comprehensive cleanup of the vLLM Ascend documentation. It fixes numerous typos, grammatical errors, and phrasing issues across community guidelines, developer documents, hardware tutorials, and feature guides. Key improvements include correcting hardware names (e.g., Atlas 300I), fixing broken links, cleaning up code examples (removing duplicate flags and trailing commas), and improving the clarity of technical explanations. These changes are necessary to ensure the documentation is professional, accurate, and easy for users to follow. Does this PR introduce any user-facing change? No, this PR contains documentation-only updates. How was this patch tested? The changes were manually reviewed for accuracy and grammatical correctness. No functional code changes were introduced. --------- Signed-off-by: herizhen <1270637059@qq.com> Signed-off-by: herizhen <59841270+herizhen@users.noreply.github.com>
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@@ -8,7 +8,7 @@ Welcome to the tutorial on optimizing Qwen Dense models in the vLLM-Ascend envir
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This document will show the main verification steps of the model, including supported features, feature configuration, environment preparation, accuracy and performance evaluation.
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The Qwen3 Dense models is first supported in [v0.8.4rc2](https://github.com/vllm-project/vllm-ascend/blob/main/docs/source/user_guide/release_notes.md#v084rc2---20250429). This example requires version **v0.11.0rc2**. Earlier versions may lack certain features.
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The Qwen3 Dense models are first supported in [v0.8.4rc2](https://github.com/vllm-project/vllm-ascend/blob/main/docs/source/user_guide/release_notes.md#v084rc2---20250429). This example requires version **v0.11.0rc2**. Earlier versions may lack certain features.
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## Supported Features
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@@ -288,7 +288,7 @@ Refer to [Using AISBench for performance evaluation](../../developer_guide/evalu
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Run performance evaluation of `Qwen3-32B-W8A8` as an example.
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Refer to [vllm benchmark](https://docs.vllm.ai/en/latest/contributing/benchmarks.html) for more details.
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Refer to [vllm benchmark](https://docs.vllm.ai/en/latest/benchmarking/) for more details.
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There are three `vllm bench` subcommands:
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