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Fix LLM getting-started.md (#10028)
Remove unnecessary line Fix ETDump part
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docs/source/llm/getting-started.md

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@@ -395,7 +395,6 @@ At this point, the working directory should contain the following files:
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If all of these are present, you can now build and run:
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```bash
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./install_executorch.sh --clean
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(mkdir cmake-out && cd cmake-out && cmake ..)
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cmake --build cmake-out -j10
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./cmake-out/nanogpt_runner
@@ -661,19 +660,15 @@ edge_config = get_xnnpack_edge_compile_config()
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# Convert to edge dialect and lower to XNNPack.
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edge_manager = to_edge_transform_and_lower(traced_model, partitioner = [XnnpackPartitioner()], compile_config = edge_config)
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et_program = edge_manager.to_executorch()
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```
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Finally, ensure that the runner links against the `xnnpack_backend` target in CMakeLists.txt.
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with open("nanogpt.pte", "wb") as file:
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file.write(et_program.buffer)
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```
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add_executable(nanogpt_runner main.cpp)
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target_link_libraries(
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nanogpt_runner
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PRIVATE
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executorch
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extension_module_static # Provides the Module class
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optimized_native_cpu_ops_lib # Provides baseline cross-platform kernels
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xnnpack_backend) # Provides the XNNPACK CPU acceleration backend
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Then run:
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```bash
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python export_nanogpt.py
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./cmake-out/nanogpt_runner
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```
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For more information, see [Quantization in ExecuTorch](../quantization-overview.md).
@@ -782,11 +777,14 @@ Run the export script and the ETRecord will be generated as `etrecord.bin`.
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An ETDump is an artifact generated at runtime containing a trace of the model execution. For more information, see [the ETDump docs](../etdump.md).
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Include the ETDump header in your code.
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Include the ETDump header and namespace in your code.
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```cpp
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// main.cpp
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#include <executorch/devtools/etdump/etdump_flatcc.h>
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using executorch::etdump::ETDumpGen;
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using torch::executor::etdump_result;
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```
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Create an Instance of the ETDumpGen class and pass it to the Module constructor.

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