Skip to main content

On-device AI across mobile, embedded and edge for PyTorch

Project description

ExecuTorch is a PyTorch platform that provides infrastructure to run PyTorch programs everywhere from AR/VR wearables to standard on-device iOS and Android mobile deployments. One of the main goals for ExecuTorch is to enable wider customization and deployment capabilities of the PyTorch programs.

The executorch pip package is in alpha.

  • Supported python versions: 3.10, 3.11
  • Compatible systems: Linux x86_64, macOS aarch64

The prebuilt executorch.extension.pybindings.portable_lib module included in this package provides a way to run ExecuTorch .pte files, with some restrictions:

Please visit the ExecuTorch website for tutorials and documentation. Here are some starting points:

  • Getting Started
    • Set up the ExecuTorch environment and run PyTorch models locally.
  • Working with local LLMs
    • Learn how to use ExecuTorch to export and accelerate a large-language model from scratch.
  • Exporting to ExecuTorch
    • Learn the fundamentals of exporting a PyTorch nn.Module to ExecuTorch, and optimizing its performance using quantization and hardware delegation.
  • Running LLaMA on iOS and Android devices.
    • Build and run LLaMA in a demo mobile app, and learn how to integrate models with your own apps.

Project details


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

executorch-0.4.0-cp312-cp312-manylinux1_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.12

executorch-0.4.0-cp312-cp312-macosx_11_0_arm64.whl (7.5 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

executorch-0.4.0-cp311-cp311-manylinux1_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.11

executorch-0.4.0-cp311-cp311-macosx_11_0_arm64.whl (7.5 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

executorch-0.4.0-cp310-cp310-manylinux1_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.10

executorch-0.4.0-cp310-cp310-macosx_11_0_arm64.whl (7.5 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

File details

Details for the file executorch-0.4.0-cp312-cp312-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp312-cp312-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 67de030fb3fa6b832d3cc014ea7ee936fc54809b5e67979bc8a7681be011bdfe
MD5 b1d96190752a4b068105f8f91bad565e
BLAKE2b-256 5d7028d9a7359012f5ad39eb7a684f695c4be0e656ebb5ddd795ce0ff920699c

See more details on using hashes here.

Provenance

File details

Details for the file executorch-0.4.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9d77f9a2e7b0e88e5fc8fe27bb9efb86b06c0972b5456eb5bcf9cff610712897
MD5 0cc8f0c1b4551a089a6da66513cea3a3
BLAKE2b-256 adb3713cffcfc57230dfa243287677aeeed9d0993f86f660eed50912231e3a7d

See more details on using hashes here.

Provenance

File details

Details for the file executorch-0.4.0-cp311-cp311-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp311-cp311-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 af6f0817917b9057a50e5d7b45932be00a7b3f5531945afb508d24f7502f0e21
MD5 081052c01ffc017dc3e19d98076bdaae
BLAKE2b-256 bc16494475b025ce14c12df6b8c488babd759ff11bec6b295cb32cad8eb4391e

See more details on using hashes here.

Provenance

File details

Details for the file executorch-0.4.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8af485760b986a83476b70471cf745631022fb4c4627c3808eaebddb98bf1408
MD5 58e093fc78b9352696d873da87459908
BLAKE2b-256 9954d13a79543d108459efb8cb8ec875b15216b3286cd21f06d30e92c5db61f5

See more details on using hashes here.

Provenance

File details

Details for the file executorch-0.4.0-cp310-cp310-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp310-cp310-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 28ad844a982e8ce2ea819b3a31f9ceea993c1c8c614d7b09eef4bae71e0f435a
MD5 083aa12ec64c7b709929e082f6090a59
BLAKE2b-256 c54a895e4173802b41b4473c9a55f13080e9b210610253155efcb532d345d50c

See more details on using hashes here.

Provenance

File details

Details for the file executorch-0.4.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for executorch-0.4.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 475aa7904dfe0ebeae92dfc4cf1a9ac6eb7e7f22e38a6b39b26a2bb19723c1e6
MD5 9e1940416f2bb981440dd8e2bcb25cc8
BLAKE2b-256 c976722cbbea64577edc34fbd85069dc75c45e8d673a34c3649f06dfe5d08fb6

See more details on using hashes here.

Provenance

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