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

Release 0.4.1.post3 - upload the config.json to PyPI (#2647)

Browse Source
This commit is contained in:
Lianmin Zheng
2024-12-29 14:25:53 -08:00
committed by GitHub
parent 1703d766d8
commit 03d5fbfd44
6 changed files with 17 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
benchmark/deepseek_v3/README.md
View File

@@ -1,8 +1,6 @@
# SGLang v0.4.1 - DeepSeek V3 Support
# DeepSeek V3 Support
We're excited to announce [SGLang v0.4.1](https://github.com/sgl-project/sglang/releases/tag/v0.4.1), which now supports [DeepSeek V3](https://huggingface.co/deepseek-ai/DeepSeek-V3-Base) - currently the strongest open-source LLM, even surpassing GPT-4o.
The SGLang and DeepSeek teams worked together to get DeepSeek V3 FP8 running on NVIDIA and AMD GPU **from day one**. We've also supported MLA optimization and DP attention before, making SGLang one of the best open-source LLM engines for running DeepSeek models.
The SGLang and DeepSeek teams worked together to get DeepSeek V3 FP8 running on NVIDIA and AMD GPUs **from day one**. SGLang also has supported [MLA optimization](https://lmsys.org/blog/2024-09-04-sglang-v0-3/#deepseek-multi-head-latent-attention-mla-throughput-optimizations) and [DP attention](https://lmsys.org/blog/2024-12-04-sglang-v0-4/#data-parallelism-attention-for-deepseek-models), making SGLang one of the best open-source LLM engines for running DeepSeek models.
Special thanks to Meituan's Search & Recommend Platform Team and Baseten's Model Performance Team for implementing the model, and DataCrunch for providing GPU resources.
@@ -20,17 +18,20 @@ If you encounter errors when starting the server, ensure the weights have finish
docker run --gpus all --shm-size 32g -p 30000:30000 -v ~/.cache/huggingface:/root/.cache/huggingface --ipc=host lmsysorg/sglang:latest \
python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code --port 30000
```
For high QPS scenarios, add the `--enable-dp-attention` argument to boost throughput.
### Using pip
```bash
# Installation
pip install "sglang[all]==0.4.1.post2" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer
pip install "sglang[all]>=0.4.1.post3" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer
# Launch
python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code
```
For high QPS scenarios, add the `--enable-dp-attention` argument to boost throughput.
### Example with OpenAI API
```python3

2
docker/Dockerfile.rocm
View File

@@ -1,5 +1,5 @@
# Usage (to build SGLang ROCm docker image):
# docker build --build-arg SGL_BRANCH=v0.4.1.post2 -t v0.4.1.post2-rocm620 -f Dockerfile.rocm .
# docker build --build-arg SGL_BRANCH=v0.4.1.post3 -t v0.4.1.post3-rocm620 -f Dockerfile.rocm .
# default base image
ARG BASE_IMAGE="rocm/vllm-dev:20241022"

4
docs/developer/setup_github_runner.md
View File

@@ -11,9 +11,9 @@ docker pull nvidia/cuda:12.1.1-devel-ubuntu22.04
# Nvidia
docker run --shm-size 128g -it -v /tmp/huggingface:/hf_home --gpus all nvidia/cuda:12.1.1-devel-ubuntu22.04 /bin/bash
# AMD
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.1.post2-rocm620 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.1.post3-rocm620 /bin/bash
# AMD just the last 2 GPUs
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.1.post2-rocm620 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.1.post3-rocm620 /bin/bash
```
### Step 2: Configure the runner by `config.sh`

10
docs/start/install.md
View File

@@ -13,7 +13,7 @@ Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/
## Method 2: From source
```
# Use the last release branch
git clone -b v0.4.1.post2 https://github.com/sgl-project/sglang.git
git clone -b v0.4.1.post3 https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
@@ -26,7 +26,7 @@ Note: To AMD ROCm system with Instinct/MI GPUs, do following instead:
```
# Use the last release branch
git clone -b v0.4.1.post2 https://github.com/sgl-project/sglang.git
git clone -b v0.4.1.post3 https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
@@ -51,7 +51,7 @@ docker run --gpus all \
Note: To AMD ROCm system with Instinct/MI GPUs, it is recommended to use `docker/Dockerfile.rocm` to build images, example and usage as below:
```bash
docker build --build-arg SGL_BRANCH=v0.4.1.post2 -t v0.4.1.post2-rocm620 -f Dockerfile.rocm .
docker build --build-arg SGL_BRANCH=v0.4.1.post3 -t v0.4.1.post3-rocm620 -f Dockerfile.rocm .
alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/dri --ipc=host \
--shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
@@ -60,11 +60,11 @@ alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/d
drun -p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
v0.4.1.post2-rocm620 \
v0.4.1.post3-rocm620 \
python3 -m sglang.launch_server --model-path meta-llama/Llama-3.1-8B-Instruct --host 0.0.0.0 --port 30000
# Till flashinfer backend available, --attention-backend triton --sampling-backend pytorch are set by default
drun v0.4.1.post2-rocm620 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
drun v0.4.1.post3-rocm620 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
```
## Method 4: Using docker compose

4
python/pyproject.toml
View File

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "sglang"
version = "0.4.1.post2"
version = "0.4.1.post3"
description = "SGLang is yet another fast serving framework for large language models and vision language models."
readme = "README.md"
requires-python = ">=3.8"
@@ -61,7 +61,7 @@ dev_hpu = ["sglang[all_hpu]", "sglang[test]"]
"Bug Tracker" = "https://github.com/sgl-project/sglang/issues"
[tool.setuptools.package-data]
"sglang" = ["srt/layers/fused_moe_triton/configs/*.json"]
"sglang" = ["srt/layers/moe/fused_moe_triton/configs/*.json", "srt/layers/quantization/configs/*.json"]
[tool.setuptools.packages.find]
exclude = [

2
python/sglang/version.py
View File

@@ -1 +1 @@
__version__ = "0.4.1.post2"
__version__ = "0.4.1.post3"