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Repository files navigation

Logo

ExecuTorch: A powerful on-device AI Framework

ContributorsStargazersJoin our Discord communityCheck out the documentation

ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.

It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).

Platform Support:

  • Operating Systems:

    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers

  • Hardware Acceleration:

    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK

Key value propositions of ExecuTorch are:

  • Portability: Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer Tools from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs, and DSPs.

Getting Started

To get started you can:

Feedback and Engagement

We welcome any feedback, suggestions, and bug reports from the community to help us improve our technology. Check out the Discussion Board or chat real time with us on Discord

Contributing

We welcome contributions. To get started review the guidelines and chat with us on Discord

Directory Structure

Please refer to the Codebase structure section of the Contributing Guidelines for more details.

License

ExecuTorch is BSD licensed, as found in the LICENSE file.

About

End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models

pytorch.org/executorch/

Resources

Readme
License

Code of conduct

Code of conduct

Contributing

Contributing
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Stars

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Watchers

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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
Contributing
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Report repository
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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
Contributing
Activity
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Watchers
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Forks
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Report repository
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pytest.ini
requirements-dev.txt
requirements-dev.txt
requirements-examples.txt
requirements-examples.txt
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Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
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var __re = new RegExp('^' + ".*" + '
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shim @ cf6a954
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.mypy.ini
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CMakePresets.json
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CODE_OF_CONDUCT.md
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README-wheel.md
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install_executorch.py
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install_executorch.sh
install_executorch.sh
install_requirements.py
install_requirements.py
install_requirements.sh
install_requirements.sh
pyproject.toml
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pytest.ini
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requirements-dev.txt
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requirements-examples.txt
requirements-examples.txt
requirements-lintrunner.txt
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run_python_script.sh
run_python_script.sh
setup.py
setup.py
version.txt
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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
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Repository files navigation
Logo
ExecuTorch: A powerful on-device AI Framework
ContributorsStargazersJoin our Discord communityCheck out the documentation
ExecuTorch is an end-to-end solution for on-device inference and training. It powers much of Meta's on-device AI experiences across Facebook, Instagram, Meta Quest, Ray-Ban Meta Smart Glasses, WhatsApp, and more.
It supports a wide range of models including LLMs (Large Language Models), CV (Computer Vision), ASR (Automatic Speech Recognition), and TTS (Text to Speech).
Platform Support:
  • Operating Systems:
    • iOS
    • Mac
    • Android
    • Linux
    • Microcontrollers
  • Hardware Acceleration:
    • Apple
    • Arm
    • Cadence
    • MediaTek
    • OpenVINO
    • Qualcomm
    • Vulkan
    • XNNPACK
Key value propositions of ExecuTorch are:
  • Portability: Compatibility with a wide variety of computing platforms,
from high-end mobile phones to highly constrained embedded systems and
microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and Developer
Tools from PyTorch model authoring and conversion, to debugging and deployment
to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance
experience due to a lightweight runtime and utilizing full hardware
capabilities such as CPUs, NPUs, and DSPs.
Getting Started
To get started you can:
Feedback and Engagement
We welcome any feedback, suggestions, and bug reports from the community to help
us improve our technology. Check out the Discussion Board or chat real time with us on Discord
Contributing
We welcome contributions. To get started review the guidelines and chat with us on Discord
Directory Structure
Please refer to the Codebase structure section of the Contributing Guidelines for more details.
License
ExecuTorch is BSD licensed, as found in the LICENSE file.
About
End-to-end solution for enabling on-device AI across mobile and edge devices for PyTorch models
pytorch.org/executorch/
Resources
Readme
License
Code of conduct
Code of conduct
Contributing
Contributing
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