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Installations

Requirements​

  • OS: Ubuntu 20.04
  • Python: 3.10
  • GPU: compute capability 7.0 or higher

Installing with pip​

# On the head node
conda create -n sllm python=3.10 -y
conda activate sllm
pip install serverless-llm
pip install serverless-llm-store

# On a worker node
conda create -n sllm-worker python=3.10 -y
conda activate sllm-worker
pip install serverless-llm[worker]
pip install serverless-llm-store
note

If you plan to use vLLM with ServerlessLLM, you need to apply our patch to the vLLM repository. Refer to the vLLM Patch section for more details.

Installing from source​

To install the package from source, follow these steps:

git clone https://github.com/ServerlessLLM/ServerlessLLM
cd ServerlessLLM
# On the head node
conda create -n sllm python=3.10 -y
conda activate sllm
pip install -e .
cd sllm_store && rm -rf build
# Installing `sllm_store` from source can be slow. We recommend using pip install.
pip install .

# On a worker node
conda create -n sllm-worker python=3.10 -y
conda activate sllm-worker
pip install -e ".[worker]"
cd sllm_store && rm -rf build
# Installing `sllm_store` from source can be slow. We recommend using pip install.
pip install .

vLLM Patch

To use vLLM with ServerlessLLM, you need to apply our patch located at sllm_store/vllm_patch/sllm_load.patch to the vLLM repository. to the vLLM repository. The patch has been tested with vLLM version 0.5.0.post1.

You can apply the patch by running the following script:

conda activate sllm-worker
./sllm_store/vllm_patch/patch.sh