Skip to main content

A high-performance LLM inference engine in Rust

Project description

The author of this package has not provided a project description

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

llm_engine_rs-0.3.1.tar.gz (19.0 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

llm_engine_rs-0.3.1-cp314-cp314-macosx_11_0_arm64.whl (633.5 kB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

llm_engine_rs-0.3.1-cp312-cp312-win_amd64.whl (638.2 kB view details)

Uploaded CPython 3.12Windows x86-64

llm_engine_rs-0.3.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (830.6 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

File details

Details for the file llm_engine_rs-0.3.1.tar.gz.

File metadata

  • Download URL: llm_engine_rs-0.3.1.tar.gz
  • Upload date:
  • Size: 19.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/1.14.1

File hashes

Hashes for llm_engine_rs-0.3.1.tar.gz
Algorithm Hash digest
SHA256 ca34cee272068acdf18d10e801e6e392e723140bb845ac20234a8fad8fa6de07
MD5 8e0d24d1be547ceff8f4d73d235f9780
BLAKE2b-256 b32d7743f46445256ca6a2ee709d1f577f67d158cf09698e42de1f6b91e8e012

See more details on using hashes here.

File details

Details for the file llm_engine_rs-0.3.1-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llm_engine_rs-0.3.1-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 cb54b04b59e8d6a0a1e0f1c52a9d70d63141767e23502b5ab0b9c6f4186db35d
MD5 8b54374886e6ed02996c4a0387b2dd4d
BLAKE2b-256 f350df9604050230ab6a382e7719fe635913fff017cd9f1c58b37f6c055650cc

See more details on using hashes here.

File details

Details for the file llm_engine_rs-0.3.1-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for llm_engine_rs-0.3.1-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 d2662b21b2e2b7f1b37cedc39ce86870a1ab831bb82b114e8ca390477b556064
MD5 ee4b33a021782e3da397a13f49c88f51
BLAKE2b-256 5bc78ba00aa57c7dc27523f7338eafef0fc58299a74c946b230a7432754f3544

See more details on using hashes here.

File details

Details for the file llm_engine_rs-0.3.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llm_engine_rs-0.3.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6a947daa99082f44d9ee7e83477f05d680b1bccdfaa6ddf5f448440945f8cbb4
MD5 b80b2c5a8d4ccc8e7fd1050104d2f920
BLAKE2b-256 e0a1fad1bbd934d76a53945a63aa7effb677bd81ed1a1093fd9832df64b1fc1c

See more details on using hashes here.

Supported by

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