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Strip .html suffix from doc links (#10210)
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docs/source/llm/getting-started.md

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# long as they adhere to the rules specified in the dynamic shape configuration.
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# Here we set the range of 0th model input's 1st dimension as
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# [0, model.config.block_size].
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# See https://pytorch.org/executorch/main/concepts.html#dynamic-shapes
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# See https://pytorch.org/executorch/main/concepts#dynamic-shapes
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# for details about creating dynamic shapes.
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dynamic_shape = (
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{1: torch.export.Dim("token_dim", max=model.config.block_size)},

examples/demo-apps/apple_ios/LLaMA/README.md

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Note: To access logs, link against the Debug build of the ExecuTorch runtime, i.e., the executorch_debug framework. For optimal performance, always link against the Release version of the deliverables (those without the _debug suffix), which have all logging overhead removed.
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For more details integrating and Running ExecuTorch on Apple Platforms, checkout this [link](https://pytorch.org/executorch/main/using-executorch-ios.html).
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For more details integrating and Running ExecuTorch on Apple Platforms, checkout this [link](https://pytorch.org/executorch/main/using-executorch-ios).
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### XCode
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* Open XCode and select "Open an existing project" to open `examples/demo-apps/apple_ios/LLama`.

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

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More details on integrating and Running ExecuTorch on Apple Platforms, check out the detailed guide [here](https://pytorch.org/executorch/main/using-executorch-ios.html#local-build).
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More details on integrating and Running ExecuTorch on Apple Platforms, check out the detailed guide [here](https://pytorch.org/executorch/main/using-executorch-ios#local-build).
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### 3. Configure Build Schemes
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We recommend that you only use the Debug build scheme during development, where you might need to access additional logs. Debug build has logging overhead and will impact inferencing performance, while release build has compiler optimizations enabled and all logging overhead removed.
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For more details integrating and Running ExecuTorch on Apple Platforms or building the package locally, checkout this [link](https://pytorch.org/executorch/main/using-executorch-ios.html).
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For more details integrating and Running ExecuTorch on Apple Platforms or building the package locally, checkout this [link](https://pytorch.org/executorch/main/using-executorch-ios).
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### 4. Build and Run the project
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examples/llm_manual/README.md

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# LLM Manual
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This repository is a storage place for the files that [LLM Manual](https://pytorch.org/executorch/main/llm/getting-started.html) needs. Please refer to the documentation website for more information.
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This repository is a storage place for the files that [LLM Manual](https://pytorch.org/executorch/main/llm/getting-started) needs. Please refer to the documentation website for more information.

examples/models/llama/README.md

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### iOS
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Please refer to [this tutorial](https://pytorch.org/executorch/main/llm/llama-demo-ios.html) to for full instructions on building the iOS LLAMA Demo App. Rename `tokenizer.model` file to `tokenizer.bin` because the demo app looks for the tokenizer file with .bin extension.
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Please refer to [this tutorial](https://pytorch.org/executorch/main/llm/llama-demo-ios) to for full instructions on building the iOS LLAMA Demo App. Rename `tokenizer.model` file to `tokenizer.bin` because the demo app looks for the tokenizer file with .bin extension.
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### Android
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Please refer to [this tutorial](https://pytorch.org/executorch/main/llm/llama-demo-android.html) to for full instructions on building the Android LLAMA Demo App.
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Please refer to [this tutorial](https://pytorch.org/executorch/main/llm/llama-demo-android) to for full instructions on building the Android LLAMA Demo App.
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## Running with low-bit kernels
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extension/benchmark/apple/Benchmark/README.md

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The Benchmark App is configured to use a Swift PM package that provides the prebuilt ExecuTorch frameworks.
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By default, the app relies on the package referencing locally built binaries. To ensure it functions correctly, you must first build the frameworks by following the [guide](https://pytorch.org/executorch/main/using-executorch-ios.html#building-from-source).
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By default, the app relies on the package referencing locally built binaries. To ensure it functions correctly, you must first build the frameworks by following the [guide](https://pytorch.org/executorch/main/using-executorch-ios#building-from-source).
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## Adding Models and Resources
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