Skip to main content

No project description provided

Project description

sllm-store

About

sllm-store is an internal library of ServerlessLLM that provides high-performance model loading from local storage into GPU memory. You can also install and use this library in your own projects, following our quick start guide.

Install with pip

pip install -i https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ sllm_store==0.0.1.dev5

Install from source

  1. Clone the repository and enter the store directory
git clone git@github.com:ServerlessLLM/ServerlessLLM.git
cd ServerlessLLM/sllm_store
  1. Install the package from source
pip install .

Build the wheel from source

To build sllm-store from source, we suggest you using the docker and build it in NVIDIA container.

  1. Clone the repository and enter the store directory:
git clone git@github.com:ServerlessLLM/ServerlessLLM.git
cd ServerlessLLM/sllm_store
  1. Build the Docker image from Dockerfile.builder
docker build -t sllm_store_builder -f Dockerfile.builder .
  1. Build the package inside the NVIDIA docker container
docker run -it --rm -v $(pwd)/dist:/app/dist sllm_store_builder /bin/bash
export PYTHON_VERSION=310
export TORCH_CUDA_ARCH_LIST="8.0 8.6 8.9 9.0"
conda activate py${PYTHON_VERSION} && python setup.py sdist bdist_wheel
  1. Install the package in local environment
pip install dist/*.whl
  1. Following the quick start guide to use the library.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

serverless_llm_store-0.5.0.tar.gz (44.6 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file serverless_llm_store-0.5.0.tar.gz.

File metadata

  • Download URL: serverless_llm_store-0.5.0.tar.gz
  • Upload date:
  • Size: 44.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.12

File hashes

Hashes for serverless_llm_store-0.5.0.tar.gz
Algorithm Hash digest
SHA256 89bdfd76f879672c5e8e61116476b8fc7edbae22b2f9e756f2fd763badcdb532
MD5 bbf840c229de6417fba613a55cfaf9a0
BLAKE2b-256 12a87dd4e318e808e5fae1482de8348441c9aa71d10046f68dc372c3ceb95e88

See more details on using hashes here.

File details

Details for the file serverless_llm_store-0.5.0-cp310-cp310-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for serverless_llm_store-0.5.0-cp310-cp310-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 904eecae78f98a4a1f325b31f5c2666636911dbdcefbf79a28a58b387a0da089
MD5 bacea54b8a49a224ca457384c0a06474
BLAKE2b-256 44dc0c8c3faea5e587bbeb4018d66a21eeedbe48eb6b6c6923ce55fa84d75f81

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page