Skip to main content

LiteRT is for mobile and embedded devices.

Project description

LiteRT is the official solution for running machine learning models on mobile and embedded devices. It enables on-device machine learning inference with low latency and a small binary size on Android, iOS, and other operating systems.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-manylinux_2_17_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_12_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.12 macOS 12.0+ ARM64

ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_10_15_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.12 macOS 10.15+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-manylinux_2_17_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_12_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.11 macOS 12.0+ ARM64

ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_10_15_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.11 macOS 10.15+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-manylinux_2_17_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_12_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.10 macOS 12.0+ ARM64

ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_10_15_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-manylinux_2_17_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_12_0_arm64.whl (2.3 MB view details)

Uploaded CPython 3.9 macOS 12.0+ ARM64

ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_10_15_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 7af56de9dadef48346828e4bd5794b7857ad54a5d4e7b6959a0d090c1ac2d441
MD5 a589e278e55a27755b885b004b3a085d
BLAKE2b-256 6ee8f5ae833a48bc5b8ab57fdff1a7b02b4724999ee7688b6d570eaf9a5664a2

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 cd3219fa65b8058bb592d1bb116fec2d2ecc35fedaddc8436dac14913a85b602
MD5 11e82a5b6f9ac8e7e1a51872bf7a5bee
BLAKE2b-256 671fba7f11198a3921f9c438db490d8bd694878fc4929d0631c296348cb37f50

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp312-cp312-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 821c7755d0a2d724d4bd815bdf057d034a7dae33dd7ad29cb81ef776246963fe
MD5 b7adb55fd77b6cb8290584f30917446f
BLAKE2b-256 f92b5254f5830c82cccc5e3297c34d249a7f4fbb79eaecab9ddec4d7749c184b

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 74859e51eb3529a840063a36f6151c4d9bd07e2a09a5d755cfc43763d88ef614
MD5 ac74c65630859e0a203f2ab53228be0e
BLAKE2b-256 98cb9e0360a427a03280c6aa9d185abc4f49d3984f9dcf6131d197f4c089264f

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 397ebd9571577e67f3585affcf7679092828ffc6d14fecb429a3c1d8960f4052
MD5 3f602d18ba2fc2c5833b22b2b25d325e
BLAKE2b-256 eba8d4a26908d1c3c7cdbcaeba276a1829d6fdc71a1f0c31a857c6ad25ee0743

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp311-cp311-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 536e18d9332262590bbd30488edcb2769389ca5cab28527cb96467c727c98772
MD5 271cfeb5a89345046aa558d1de6a6da7
BLAKE2b-256 0b78dcf66ae0f154d7312ddb507ae4c98d823289e6431d635fbaf6da108db8fb

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 f138c980ad1e1b070d063808bffa5ad8228e7de05bd92d7da46ff838a9ec69a2
MD5 daeef9a67ec63a50428b8838e04d11be
BLAKE2b-256 4f45094089b5e724f96a73b007f90b28aa8759c9bc3c2e72b8302621d566fcbf

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 467ec82b850b9b84ebafd5a5f044a510584cc45c821083b807f94ff0a03b3df5
MD5 82ef50d54e637aa4dcaf1c5764193614
BLAKE2b-256 e3170e24fbe39f4ff603c95701cba3e97ec71053522c09c2a03fb03ed7148f10

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 2adb984341cb4cb8ba5f044433d3cda3068dc48c87b57be8b2a49235c179ebf5
MD5 6ec385c2c6a9050920c93525ca31ee14
BLAKE2b-256 008c4272eba404758184c694e847e5a4c779452eab681987306ccce310a577a9

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 ca2d29c8adde8536d5794f80445310e3301534f71333d8408159bd77f3ded28a
MD5 b41cc38b49639abf734a2d86bd526ce3
BLAKE2b-256 5606ff549cdd90ca4e3353a43986e04e24974689111494934e13d9f53f9ffc9c

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 d5e32b9766929f6e5f9c195d71d71c8f7b31e3055c38f057976fbfb880643f7c
MD5 20d4771ee5fb4396d726242bc666b991
BLAKE2b-256 72490942faf9c5f89960eec039745fa3a7c665889923c08c7c345630c8e2395e

See more details on using hashes here.

File details

Details for the file ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for ai_edge_litert_nightly-1.0.1.dev20240908-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 01a7cffdd3deb64d67b668ba917c00efe6d3c64f9637f27b3fc3ce46c07271a4
MD5 dd674a07796f197fca6ca40a0491a3aa
BLAKE2b-256 b31556644fe4e5f1d8753ff2cc36e9b8d3cd7418bee5f743c6775e2e25df0e4f

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