EngineX-Hygon/sglang
5
0
Fork 0
Code Issues Pull Requests Actions 7 Projects Releases Wiki Activity

Misc clean up; Remove the support of jump forward (#4032)

Browse Source
This commit is contained in:
Lianmin Zheng
2025-03-03 07:02:14 -08:00
committed by GitHub
parent 110e006673
commit 935cda944b
41 changed files with 396 additions and 426 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
docs/start/install.md
View File

@@ -2,9 +2,10 @@
You can install SGLang using any of the methods below.
For running DeepSeek V3/R1, refer to [DeepSeek V3 Support](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3). It is recommended to use the [latest version](https://pypi.org/project/sglang/#history) and deploy it with [Docker](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3#using-docker-recommended) to avoid environment-related problems.
For running DeepSeek V3/R1, refer to [DeepSeek V3 Support](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3). It is recommended to use the latest version and deploy it with [Docker](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3#using-docker-recommended) to avoid environment-related issues.
It is recommended to use uv to install the dependencies for faster installation:
We recommend using uv to install the dependencies with a higher installation speed:
## Method 1: With pip or uv
```bash
@@ -13,14 +14,13 @@ pip install uv
uv pip install "sglang[all]>=0.4.3.post2" --find-links https://flashinfer.ai/whl/cu124/torch2.5/flashinfer-python
```
**Quick Fixes to Installation**
**Quick Fixes to Common Problems**
- SGLang currently uses torch 2.5, so you need to install flashinfer for torch 2.5. 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`, please try either of the following solutions:
1. Use `export CUDA_HOME=/usr/local/cuda-<your-cuda-version>` to set the `CUDA_HOME` environment variable.
2. Install FlashInfer first following [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html), then install SGLang as described above.
- 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:
1. Use `export CUDA_HOME=/usr/local/cuda-<your-cuda-version>` to set the `CUDA_HOME` environment variable.
2. Install FlashInfer first following [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html), then install SGLang as described above.
- If you encounter `ImportError; cannot import name 'is_valid_list_of_images' from 'transformers.models.llama.image_processing_llama'`, try to use the specified version of `transformers` in [pyproject.toml](https://github.com/sgl-project/sglang/blob/main/python/pyproject.toml). Currently, just running `pip install transformers==4.48.3`.