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
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file litert_converter-0.3.0.dev20260703-cp314-cp314-macosx_12_0_arm64.whl.
File metadata
- Download URL: litert_converter-0.3.0.dev20260703-cp314-cp314-macosx_12_0_arm64.whl
- Upload date:
- Size: 103.6 MB
- Tags: CPython 3.14, macOS 12.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ad3db5f652ca8f7b3897b8137dba6b33a6cf1ae46a5525d9361fc4765e29900f
|
|
| MD5 |
e39f45d03fffe1d5cdfcd43e000f97ee
|
|
| BLAKE2b-256 |
95c48cc9574e99d13179a0bd306c03d9295b91f9d4c8d9d6bf1f60221622986e
|
File details
Details for the file litert_converter-0.3.0.dev20260703-cp313-cp313-macosx_12_0_arm64.whl.
File metadata
- Download URL: litert_converter-0.3.0.dev20260703-cp313-cp313-macosx_12_0_arm64.whl
- Upload date:
- Size: 103.6 MB
- Tags: CPython 3.13, macOS 12.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
916b11a171def35d55fca05cb2eca970288937eef00ae9c2e14d4779569a6823
|
|
| MD5 |
41915bf430df754411125bd0f4709cff
|
|
| BLAKE2b-256 |
7f58fb10a16bfd5a7b613945f4d8f3e5857f59f7194327fe38be693d4d29c0af
|
File details
Details for the file litert_converter-0.3.0.dev20260703-cp312-cp312-macosx_12_0_arm64.whl.
File metadata
- Download URL: litert_converter-0.3.0.dev20260703-cp312-cp312-macosx_12_0_arm64.whl
- Upload date:
- Size: 103.6 MB
- Tags: CPython 3.12, macOS 12.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d52100f05f41f3d8af6913a89ebd19ba8ca6d4b18143a9018fdf83378c930934
|
|
| MD5 |
610c6842825dc39397026ab06be0182c
|
|
| BLAKE2b-256 |
e42bcd5553d6d60d4d2ab2b6c1950107ded8453013954b0cab11a6c452e5bf1c
|
File details
Details for the file litert_converter-0.3.0.dev20260703-cp311-cp311-macosx_12_0_arm64.whl.
File metadata
- Download URL: litert_converter-0.3.0.dev20260703-cp311-cp311-macosx_12_0_arm64.whl
- Upload date:
- Size: 103.6 MB
- Tags: CPython 3.11, macOS 12.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f6413c134467741a9f2b3cd250b051af2baee85e99936fc02fc438731b046653
|
|
| MD5 |
d745df94a1226721c923a3b8ac59153b
|
|
| BLAKE2b-256 |
de6134ef19f04548b999e7bc7a3d4e1bba41cb3f411c616d51612283b92d3ce3
|
File details
Details for the file litert_converter-0.3.0.dev20260703-cp310-cp310-macosx_12_0_arm64.whl.
File metadata
- Download URL: litert_converter-0.3.0.dev20260703-cp310-cp310-macosx_12_0_arm64.whl
- Upload date:
- Size: 103.5 MB
- Tags: CPython 3.10, macOS 12.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
be29f364abc06c3831f68e0370804b78645650c7accf68e1e52e1dec7c8f3623
|
|
| MD5 |
d18aa3d1dc82a714ff1c2b6432b7eec9
|
|
| BLAKE2b-256 |
e4db01601f701d0e4c4862ab4bf6f4ad5bb99e757c1df7ffa0fa04ef10ac4b92
|
