d425a0d0e9
* [Docs] Fix app.readthedocs buliding Signed-off-by: dongxinyu03 <dongxinyu03@baidu.com> * [Docs] Add vLLM-Kunlun New Model Adaptation Manual and Update Model Support Signed-off-by: dongxinyu03 <dongxinyu03@baidu.com>
2.2 KiB
Welcome to vLLM Kunlun Plugin
:::{figure} ./logos/vllm-kunlun-logo-text-light.png :align: center :alt: vLLM :class: no-scaled-link :width: 70% :::
:::{raw} html
vLLM Kunlun Plugin
<script async defer src="https://buttons.github.io/buttons.js"></script> Star Watch Fork
:::vLLM Kunlun (vllm-kunlun) is a community-maintained hardware plugin designed to seamlessly run vLLM on the Kunlun XPU. It is the recommended approach for integrating the Kunlun backend within the vLLM community, adhering to the principles outlined in the [RFC]: Hardware pluggable. This plugin provides a hardware-pluggable interface that decouples the integration of the Kunlun XPU with vLLM.
By utilizing the vLLM Kunlun plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, and Multi-modal LLMs, can run effortlessly on the Kunlun XPU.
Documentation
% How to start using vLLM on Kunlun XPU? :::{toctree} :caption: Getting Started :maxdepth: 1 quick_start installation tutorials/index.md faqs :::
% What does vLLM Kunlun Plugin support? :::{toctree} :caption: User Guide :maxdepth: 1 user_guide/support_matrix/index user_guide/configuration/index user_guide/feature_guide/index user_guide/release_notes :::
% How to contribute to the vLLM Kunlun project :::{toctree} :caption: Developer Guide :maxdepth: 1 developer_guide/developer_guide developer_guide/contribution/index developer_guide/feature_guide/index developer_guide/evaluation/index developer_guide/performance/index :::
% How to involve vLLM Kunlun :::{toctree} :caption: Community :maxdepth: 1 community/governance community/contributors community/versioning_policy community/user_stories/index :::