- SGLang currently uses torch 2.6, so you need to install flashinfer for torch 2.6. If you want to install flashinfer separately, please refer to [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html). Please note that the FlashInfer pypi package is called `flashinfer-python` instead of `flashinfer`.
- SGLang currently uses torch 2.7.1, so you need to install flashinfer for torch 2.7.1. If you want to install flashinfer separately, please refer to [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html). Please note that the FlashInfer pypi package is called `flashinfer-python` instead of `flashinfer`.
- If you encounter `OSError: CUDA_HOME environment variable is not set`. Please set it to your CUDA install root with either of the following solutions:
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@@ -34,7 +34,7 @@ pip install --upgrade pip
pip install-e"python[all]"
```
Note: SGLang currently uses torch 2.6, so you need to install flashinfer for torch 2.6. If you want to install flashinfer separately, please refer to [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html).
Note: SGLang currently uses torch 2.7.1, so you need to install flashinfer for torch 2.7.1. If you want to install flashinfer separately, please refer to [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html).
If you want to develop SGLang, it is recommended to use docker. Please refer to [setup docker container](https://github.com/sgl-project/sglang/blob/main/docs/references/development_guide_using_docker.md#setup-docker-container) for guidance. The docker image is `lmsysorg/sglang:dev`.
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@@ -162,4 +162,4 @@ sky status --endpoint 30000 sglang
-[FlashInfer](https://github.com/flashinfer-ai/flashinfer) is the default attention kernel backend. It only supports sm75 and above. If you encounter any FlashInfer-related issues on sm75+ devices (e.g., T4, A10, A100, L4, L40S, H100), please switch to other kernels by adding `--attention-backend triton --sampling-backend pytorch` and open an issue on GitHub.
- If you only need to use OpenAI models with the frontend language, you can avoid installing other dependencies by using `pip install "sglang[openai]"`.
- The language frontend operates independently of the backend runtime. You can install the frontend locally without needing a GPU, while the backend can be set up on a GPU-enabled machine. To install the frontend, run `pip install sglang`, and for the backend, use `pip install sglang[srt]`. `srt` is the abbreviation of SGLang runtime.
- To reinstall flashinfer locally, use the following command: `pip install "flashinfer-python==0.2.5" -i https://flashinfer.ai/whl/cu124/torch2.6 --force-reinstall --no-deps` and then delete the cache with `rm -rf ~/.cache/flashinfer`.
- To reinstall flashinfer locally, use the following command: `pip3 install --upgrade flashinfer-python --force-reinstall --no-deps` and then delete the cache with `rm -rf ~/.cache/flashinfer`.
