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Audit and update the pip package metadata #3265
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@@ -0,0 +1,25 @@ | ||
**ExecuTorch** is a [PyTorch](https://pytorch.org/) 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. | ||
|
||
Please visit the [ExecuTorch website](https://pytorch.org/executorch/) for | ||
tutorials and documentation. Here are some starting points: | ||
* [Getting | ||
Started](https://pytorch.org/executorch/stable/getting-started-setup.html) | ||
* Set up the ExecuTorch environment and run PyTorch models locally. | ||
* [Working with | ||
local LLMs](https://pytorch.org/executorch/stable/llm/getting-started.html) | ||
* Learn how to use ExecuTorch to export and accelerate a large-language model | ||
from scratch. | ||
* [Exporting to | ||
ExecuTorch](https://pytorch.org/executorch/main/tutorials/export-to-executorch-tutorial.html) | ||
* Learn the fundamentals of exporting a PyTorch `nn.Module` to ExecuTorch, and | ||
optimizing its performance using quantization and hardware delegation. | ||
* Running LLaMA on | ||
[iOS](https://pytorch.org/executorch/stable/llm/llama-demo-ios.html) and | ||
[Android](https://pytorch.org/executorch/stable/llm/llama-demo-android.html) | ||
devices. | ||
* Build and run LLaMA in a demo mobile app, and learn how to integrate models | ||
with your own apps. |
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@@ -15,7 +15,38 @@ dynamic = [ | |
# setup.py will set the version. | ||
'version', | ||
] | ||
# Python dependencies required for development | ||
description = "On-device AI across mobile, embedded and edge for PyTorch" | ||
readme = "README-wheel.md" | ||
authors = [ | ||
{name="PyTorch Team", email="[email protected]"}, | ||
] | ||
license = {file = "LICENSE"} | ||
keywords = ["pytorch", "machine learning"] | ||
# PyPI package information. | ||
classifiers = [ | ||
# How mature is this project? Common values are | ||
# 3 - Alpha | ||
# 4 - Beta | ||
# 5 - Production/Stable | ||
"Development Status :: 3 - Alpha", | ||
"Intended Audience :: Developers", | ||
"Intended Audience :: Education", | ||
"Intended Audience :: Science/Research", | ||
"License :: OSI Approved :: BSD License", | ||
"Topic :: Scientific/Engineering", | ||
"Topic :: Scientific/Engineering :: Mathematics", | ||
"Topic :: Scientific/Engineering :: Artificial Intelligence", | ||
"Topic :: Software Development", | ||
"Topic :: Software Development :: Libraries", | ||
"Topic :: Software Development :: Libraries :: Python Modules", | ||
"Programming Language :: C++", | ||
"Programming Language :: Python :: 3", | ||
# Update this as we support more versions of python. | ||
"Programming Language :: Python :: 3.10", | ||
] | ||
|
||
# Python dependencies required for use. | ||
requires-python = ">=3.10" | ||
dependencies=[ | ||
"expecttest", | ||
"flatbuffers", | ||
|
@@ -32,6 +63,13 @@ dependencies=[ | |
"tabulate", | ||
] | ||
|
||
[project.urls] | ||
# The keys are arbitrary but will be visible on PyPI. | ||
Homepage = "https://pytorch.org/executorch/" | ||
Repository = "https://github.com/pytorch/executorch" | ||
Issues = "https://github.com/pytorch/executorch/issues" | ||
Changelog = "https://github.com/pytorch/executorch/releases" | ||
|
||
# Tell setuptools to generate commandline wrappers for tools that we install | ||
# under data/bin in the pip package. This will put these commands on the user's | ||
# path. | ||
|
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These llm URLs don't work yet, but they will when we go live. I tested by replacing "stable" with "0.2" in each URL -- when we go live, we'll update the "stable" symlink to point to "0.2" in the gh-pages branch.