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@@ -43,9 +43,11 @@ Conformer is a popular Neural Network for speech recognition. This repository co
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  ## Uses
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- You need to install ExecuTorch 1.0 with $ pip install executorch.
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- By downloading the quantized exported graph module, you can directly call the to_edge_transform_and_lower API of ExecuTorch. This will produce a pte file for your variant of the Ethos-U. Example for producing a pte file for an Ethos-U85 with 256 MACs in Shared_Sram memory mode:
 
 
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  Below is an example script to produce a pte file for Ethos-U85 256 MAC configuration in Shared_Sram memory mode.
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  ```
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  import torch
@@ -94,21 +96,6 @@ if __name__ == "__main__":
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  ```
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
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  ## Uses
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+ You need to install ExecuTorch 1.0 with `$ pip install executorch`.
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+ By downloading the quantized exported graph module, you can directly call the `to_edge_transform_and_lower` API of ExecuTorch.
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+ The `to_edge_transform_and_lower` API will convert the quantized exported program to backend-specific command stream for the Ethos-U.
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+ The end result a pte file for your variant of the Ethos-U.
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  Below is an example script to produce a pte file for Ethos-U85 256 MAC configuration in Shared_Sram memory mode.
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  ```
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  import torch
 
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  ```
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->