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

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

litert_converter-0.3.0.dev20260706-cp314-cp314-macosx_12_0_arm64.whl (103.6 MB view details)

Uploaded CPython 3.14macOS 12.0+ ARM64

litert_converter-0.3.0.dev20260706-cp313-cp313-macosx_12_0_arm64.whl (103.6 MB view details)

Uploaded CPython 3.13macOS 12.0+ ARM64

litert_converter-0.3.0.dev20260706-cp312-cp312-macosx_12_0_arm64.whl (103.6 MB view details)

Uploaded CPython 3.12macOS 12.0+ ARM64

litert_converter-0.3.0.dev20260706-cp311-cp311-macosx_12_0_arm64.whl (103.6 MB view details)

Uploaded CPython 3.11macOS 12.0+ ARM64

litert_converter-0.3.0.dev20260706-cp310-cp310-macosx_12_0_arm64.whl (103.5 MB view details)

Uploaded CPython 3.10macOS 12.0+ ARM64

File details

Details for the file litert_converter-0.3.0.dev20260706-cp314-cp314-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for litert_converter-0.3.0.dev20260706-cp314-cp314-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 ac7259622b2c12cd2f0d07b935443d3bd1b8067c223933b27b294891753ed118
MD5 a08a9a81b8fd096bdb7309e26f838c87
BLAKE2b-256 7bbf2ff9d3436151494b589f66b4f6f05e3cc5d24083891a309818077570de69

See more details on using hashes here.

File details

Details for the file litert_converter-0.3.0.dev20260706-cp313-cp313-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for litert_converter-0.3.0.dev20260706-cp313-cp313-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 810d777ff37e5909fbe21f11333799d6b926f62b668401603ff83fccc8136a63
MD5 f318ef6e84e5268b6ecccf35e5dc4ec8
BLAKE2b-256 c90e7dade6f5e2f63a59a9c8937e502661a497e3880b03475f59d06faa672e12

See more details on using hashes here.

File details

Details for the file litert_converter-0.3.0.dev20260706-cp312-cp312-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for litert_converter-0.3.0.dev20260706-cp312-cp312-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 9a496ac032f6b05e9a13323d0643970be573dd1cbc343416ee66e8ec885a9d49
MD5 041c1914df80c7e0a22d416fd057b2fe
BLAKE2b-256 616f8fbf231892943b8022010e9b33463413bcf4badbf2f7dcd32fb1b174ad3a

See more details on using hashes here.

File details

Details for the file litert_converter-0.3.0.dev20260706-cp311-cp311-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for litert_converter-0.3.0.dev20260706-cp311-cp311-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 19827c32d5e29f173bdddd35706b5b2ac2dc5b3eb40c78fb7e934a5fffc4d56b
MD5 0abca9bb7a3fee8203f60b4749b557a6
BLAKE2b-256 f5a25b6ff7fc8f6213bb081408ef3d0ea18d899a178caa7545a5e9f751e0a36e

See more details on using hashes here.

File details

Details for the file litert_converter-0.3.0.dev20260706-cp310-cp310-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for litert_converter-0.3.0.dev20260706-cp310-cp310-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 69db81a1671a29584a9d2bd0afe691aa5117c0206c6a13c95815ba7c496906e3
MD5 b077ea97b65f8df364553ed783a921d8
BLAKE2b-256 54ad8fc7cba4bcbd1f2b834ff8d4bf3011e009c5cd732210900c5f7bef97351f

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