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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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## Prerequisites
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### Support Devices
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- Atlas A2 Training series (Atlas 800T A2, Atlas 900 A2 PoD, Atlas 200T A2 Box16, Atlas 300T A2)
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- Atlas 800I A2 Inference series (Atlas 800I A2)
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### Dependencies
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| Requirement | Supported version | Recommended version | Note |
See [Building and Testing](./CONTRIBUTING.md) for more details, which is a step-by-step guide to help you set up development environment, build and test.
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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## Contents
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-[Quick Start](./quick_start.md)
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-[Installation](./installation.md)
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- Usage
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-[Running vLLM with Ascend](./usage/running_vllm_with_ascend.md)
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