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@@ -39,7 +39,7 @@ By using vLLM Ascend plugin, popular open-source models, including Transformer-l
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* PyTorch >= 2.4.0, torch-npu >= 2.4.0
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* vLLM (the same version as vllm-ascend)
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Find more about how to setup your environment step by step in [here](docs/installation.md).
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Find more about how to setup your environment step by step in [here](docs/source/installation.md).
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## Getting Started
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vllm serve Qwen/Qwen2.5-0.5B-Instruct
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curl http://localhost:8000/v1/models
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```
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**Please refer to [official docs](./docs/index.md) for more details.**
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**Please refer to [official docs](https://vllm-ascend.readthedocs.io/en/latest/) for more details.**
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## Contributing
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See [CONTRIBUTING](docs/source/developer_guide/contributing.md) for more details, which is a step-by-step guide to help you set up development environment, build and test.
| Python | >= 3.9 |[3.10](https://www.python.org/downloads/)| Required for vllm |
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| CANN | >= 8.0.RC2 |[8.0.RC3](https://www.hiascend.com/developer/download/community/result?module=cann&cann=8.0.0.beta1)| Required for vllm-ascend and torch-npu |
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| torch-npu | >= 2.4.0 |[2.5.1rc1](https://gitee.com/ascend/pytorch/releases/tag/v6.0.0.alpha001-pytorch2.5.1)| Required for vllm-ascend |
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| torch | >= 2.4.0 |[2.5.1](https://github.com/pytorch/pytorch/releases/tag/v2.5.1)| Required for torch-npu and vllm required |
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This document describes how to install vllm-ascend manually.
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## Prepare Ascend NPU environment
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## Requirements
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Below is a quick note to install recommended version software:
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- OS: Linux
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- Python: 3.10 or higher
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- A hardware with Ascend NPU. It's usually the Atlas 800 A2 series.
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- Software:
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### Containerized installation
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| Software | Supported version | Note |
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| ------------ | ----------------- | ---- |
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| CANN | >= 8.0.0.beta1 | Required for vllm-ascend and torch-npu |
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| torch-npu | >= 2.5.1rc1 | Required for vllm-ascend |
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| torch | >= 2.5.1 | Required for torch-npu and vllm |
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You can use the [container image](https://hub.docker.com/r/ascendai/cann) directly with one line command:
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## Configure a new environment
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Before installing the package, you need to make sure firmware/driver and CANN is installed correctly.
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### Install firmwares and drivers
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To verify that the Ascend NPU firmware and driver were correctly installed, run `npu-smi` info
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> Tips: Refer to [Ascend Environment Setup Guide](https://ascend.github.io/docs/sources/ascend/quick_install.html) for more details.
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### Install CANN (optional)
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The installation of CANN wouldn’t be necessary if you are using a CANN container image, you can skip this step.If you want to install vllm-ascend on a bare environment by hand, you need install CANN first.
sh Ascend-cann-kernels-910b_8.0.0_linux-aarch64.run --full
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```
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Once it's done, you can read either **Set up using Python** or **Set up using Docker** section to install and use vllm-ascend.
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## Set up using Python
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> Notes: If you are installing vllm-ascend on an arch64 machine, The `-f https://download.pytorch.org/whl/torch/` command parameter in this section can be omitted. It's only used for find torch package on x86 machine.
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Please make sure that CANN is installed. It can be done by **Configure a new environment** step. Or by using an CANN container directly:
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```bash
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# Setup a CANN container using docker
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# Update DEVICE according to your device (/dev/davinci[0-7])
You do not need to install `torch` and `torch_npu` manually, they will be automatically installed as `vllm-ascend` dependencies.
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Then you can install vllm-ascend from **pre-built wheel** or **source code**.
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### Install from Pre-built wheels (Not support yet)
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### Manual installation
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1. Install vllm
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Or follow the instructions provided in the [Ascend Installation Guide](https://ascend.github.io/docs/sources/ascend/quick_install.html)to set up the environment.
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Since vllm on pypi is not compatible with cpu, we need to install vllm from source code.
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