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Fix broken links on the coreml tutorial page (#3250)
Summary: Pull Request resolved: #3250 Differential Revision: D56487125
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docs/source/build-run-coreml.md

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# Building and Running ExecuTorch with Core ML Backend
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Core ML delegate uses Core ML APIs to enable running neural networks via Apple's hardware acceleration. For more about coreml you can read [here](https://developer.apple.com/documentation/coreml). In this tutorial, we will walk through the steps of lowering a PyTorch model to Core ML delegate
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Core ML delegate uses Core ML APIs to enable running neural networks via Apple's hardware acceleration. For more about Core ML you can read [here](https://developer.apple.com/documentation/coreml). In this tutorial, we will walk through the steps of lowering a PyTorch model to Core ML delegate
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In order to be able to successfully build and run the ExecuTorch's Core ML backend you'll need the following hardware and software components.
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### Hardware:
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- A [mac](https://www.apple.com/mac/]) system for building.
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- A [mac](https://www.apple.com/mac/]) or [iPhone](https://www.apple.com/iphone/) or [iPad](https://www.apple.com/ipad/) or [Apple TV](https://www.apple.com/tv-home/) device for running the model.
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- A [mac](https://www.apple.com/mac/) system for building.
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- A [mac](https://www.apple.com/mac/) or [iPhone](https://www.apple.com/iphone/) or [iPad](https://www.apple.com/ipad/) or [Apple TV](https://www.apple.com/tv-home/) device for running the model.
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### Software:
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# Builds `coreml_executor_runner`.
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./examples/apple/coreml/scripts/build_executor_runner.sh
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```
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3. Run and generate an [ETDump](./sdk-etdump.md).
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3. Run and generate an [ETDump](./sdk-etdump.md).
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```bash
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cd executorch
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