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25 changes: 25 additions & 0 deletions README-wheel.md
Original file line number Diff line number Diff line change
@@ -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)
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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.

* 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.
40 changes: 39 additions & 1 deletion pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -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",
Expand All @@ -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.
Expand Down