affca6f348
### What this PR does / why we need it?
1. Provide accuracy test report for development branch release.
2. Models and datasets for accuracy test：
| Model | datasets |
|---------------------------- | --------------------------- |
| Qwen2.5-7B-Instruct | ceval-val, gsm8k, mmlu |
| Qwen3-8B | ceval-val, gsm8k, mmlu |
| Llama-3.1-8B-Instruct | ceval-val, gsm8k, mmlu |
| Qwen2.5-VL-7B-Instruct | mmmu_val |
### Does this PR introduce _any_ user-facing change?
This PR will display the accuracy test report of the release versionin
docs/source/developer_guide/accuracy_report。
Qwen2.5-7B-Instruct.md
Qwen3-8B.md
Llama-3.1-8B-Instruct.md
Qwen2.5-VL-7B-Instruct .md
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
67 lines
2.0 KiB
Markdown
67 lines
2.0 KiB
Markdown
# Welcome to vLLM Ascend Plugin
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:::{figure} ./logos/vllm-ascend-logo-text-light.png
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:align: center
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:alt: vLLM
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:class: no-scaled-link
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:width: 70%
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:::
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:::{raw} html
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<p style="text-align:center">
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<strong>vLLM Ascend Plugin
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</strong>
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</p>
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<p style="text-align:center">
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<script async defer src="https://buttons.github.io/buttons.js"></script>
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<a class="github-button" href="https://github.com/vllm-project/vllm-ascend" data-show-count="true" data-size="large" aria-label="Star">Star</a>
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<a class="github-button" href="https://github.com/vllm-project/vllm-ascend/subscription" data-icon="octicon-eye" data-size="large" aria-label="Watch">Watch</a>
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<a class="github-button" href="https://github.com/vllm-project/vllm-ascend/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork">Fork</a>
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</p>
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:::
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vLLM Ascend plugin (vllm-ascend) is a community maintained hardware plugin for running vLLM on the Ascend NPU.
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This plugin is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [[RFC]: Hardware pluggable](https://github.com/vllm-project/vllm/issues/11162), providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.
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By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.
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## Documentation
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% How to start using vLLM on Ascend NPU?
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:::{toctree}
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:caption: Getting Started
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:maxdepth: 1
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quick_start
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installation
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tutorials/index.md
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faqs
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:::
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% What does vLLM Ascend Plugin support?
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:::{toctree}
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:caption: User Guide
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:maxdepth: 1
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user_guide/suppoted_features
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user_guide/supported_models
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user_guide/env_vars
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user_guide/release_notes
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:::
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% How to contribute to the vLLM Ascend project
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:::{toctree}
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:caption: Developer Guide
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:maxdepth: 1
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developer_guide/contributing
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developer_guide/versioning_policy
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developer_guide/evaluation/index
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:::
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% User stories about vLLM Ascend project
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:::{toctree}
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:caption: User Story
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:maxdepth: 1
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user_stories/index
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:::
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