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| 1 | +# Awesome OpenXLA |
| 2 | + |
| 3 | +<picture> |
| 4 | + <source |
| 5 | + media="(prefers-color-scheme: dark)" |
| 6 | + srcset="https://raw.githubusercontent.com/openxla/xla/refs/heads/main/docs/images/openxla_dark.svg" |
| 7 | + class="devsite-dark-theme"> |
| 8 | + <img |
| 9 | + alt="OpenXLA Ecosystem" |
| 10 | + src="https://raw.githubusercontent.com/openxla/xla/refs/heads/main/docs/images/openxla.svg"> |
| 11 | +</picture> |
| 12 | + |
| 13 | +[OpenXLA](https://openxla.org) is open ecosystem of performant, portable, and |
| 14 | +extensible machine learning (ML) infrastructure components that simplify ML |
| 15 | +development by defragmenting the tools between frontend frameworks and hardware |
| 16 | +backends. Built by industry leaders in AI modeling, software, and hardware. |
| 17 | + |
| 18 | +**How is the community using OpenXLA?** This page consolidates links to |
| 19 | +repositories and projects using OpenXLA to provide inspiration and code pointers! |
| 20 | + |
| 21 | +**Have a project that uses OpenXLA?** Send us a pull request and add it to this page! |
| 22 | + |
| 23 | +## Frameworks |
| 24 | + |
| 25 | +- [JAX](https://github.com/jax-ml/jax) is a ML framework with a |
| 26 | +NumPy-like API for writing high-performance ML models <img align="center" src="https://img.shields.io/github/stars/jax-ml/jax?style=social"> |
| 27 | +- [PyTorch/XLA](https://github.com/pytorch/xla/) provides a bridge from PyTorch |
| 28 | +to OpenXLA and StableHLO <img align="center" src="https://img.shields.io/github/stars/pytorch/xla?style=social"> |
| 29 | +- [TensorFlow](https://github.com/tensorflow/tensorflow) is a long-standing ML |
| 30 | +framework with a large ecosystem <img align="center" src="https://img.shields.io/github/stars/tensorflow/tensorflow?style=social"> |
| 31 | + |
| 32 | +## PJRT Plugins |
| 33 | + |
| 34 | +- [libTPU](https://cloud.google.com/tpu/docs/runtimes) allows models to execute |
| 35 | +on Google's Cloud TPUs |
| 36 | + |
| 37 | +## Edge Compilation |
| 38 | + |
| 39 | +- [Google AI Edge](https://ai.google.dev/edge) uses StableHLO as an input format |
| 40 | +to deploy to mobile devices using [LiteRT](https://ai.google.dev/edge/litert) |
| 41 | + - [AI Edge Torch](https://github.com/google-ai-edge/ai-edge-torch) exports |
| 42 | + PyTorch models for mobile deployment via StableHLO <img align="center" src="https://img.shields.io/github/stars/google-ai-edge/ai-edge-torch?style=social"> |
| 43 | + |
| 44 | +## Tooling and Visualization |
| 45 | + |
| 46 | +- [Model Explorer](https://github.com/google-ai-edge/model-explorer) offers |
| 47 | +heirarchical graph visualization with support for StableHLO models |
| 48 | +<img align="center" src="https://img.shields.io/github/stars/google-ai-edge/model-explorer?style=social"> |
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