58 lines
1.4 KiB
ReStructuredText
58 lines
1.4 KiB
ReStructuredText
.. _installation:
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Installation
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============
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vLLM is a Python library that also contains some C++ and CUDA code.
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This additional code requires compilation on the user's machine.
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Requirements
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------------
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* OS: Linux
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* Python: 3.8 or higher
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* CUDA: 11.0 -- 11.8
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* GPU: compute capability 7.0 or higher (e.g., V100, T4, RTX20xx, A100, L4, etc.)
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.. note::
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As of now, vLLM does not support CUDA 12.
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If you are using Hopper or Lovelace GPUs, please use CUDA 11.8 instead of CUDA 12.
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.. tip::
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If you have trouble installing vLLM, we recommend using the NVIDIA PyTorch Docker image.
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.. code-block:: console
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$ # Pull the Docker image with CUDA 11.8.
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$ docker run --gpus all -it --rm --shm-size=8g nvcr.io/nvidia/pytorch:22.12-py3
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Inside the Docker container, please execute :code:`pip uninstall torch` before installing vLLM.
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Install with pip
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----------------
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You can install vLLM using pip:
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.. code-block:: console
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$ # (Optional) Create a new conda environment.
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$ conda create -n myenv python=3.8 -y
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$ conda activate myenv
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$ # Install vLLM.
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$ pip install vllm # This may take 5-10 minutes.
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.. _build_from_source:
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Build from source
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-----------------
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You can also build and install vLLM from source:
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.. code-block:: console
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$ git clone https://github.com/vllm-project/vllm.git
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$ cd vllm
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$ pip install -e . # This may take 5-10 minutes.
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