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Updated README.md with torchdata project status. #1197

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8 changes: 2 additions & 6 deletions README.md
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# TorchData
# TorchData (see note below on current status)

[**Why TorchData?**](#why-composable-data-loading) | [**Install guide**](#installation) |
[**What are DataPipes?**](#what-are-datapipes) | [**Beta Usage and Feedback**](#beta-usage-and-feedback) |
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[**Contributing**](#contributing) | [**Future Plans**](#future-plans)

**This library is currently in the Beta stage and new features are under active development. The API may change based on
user feedback or performance. We are committed to bring this library to stable release, but a few future changes may not
be completely backward compatible. If you install from source or use the nightly version of this library, use it along
with the PyTorch nightly binaries. If you have suggestions on the API or use cases you'd like to be covered, please open
a GitHub issue. We'd love to hear thoughts and feedback.**
**:warning: As of July 2023, we have paused active development on TorchData and have paused new releases. We have learnt a lot from building it and hearing from users, but also believe we need to re-evaluate the technical design and approach given how much the industry has changed since we began the project. During the rest of 2023 we will be re-evaluating our plans in this space. Please reach out if you suggestions or comments (please use [#1196](https://github.com/pytorch/data/issues/1196) for feedback).**

`torchdata` is a library of common modular data loading primitives for easily constructing flexible and performant data
pipelines.
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