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Update release branch in Burn book

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syl20bnr 2024-08-27 15:17:25 -04:00
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burn-book/src/basic-workflow/README.md
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@ -4,7 +4,7 @@ This guide will walk you through the process of creating a custom model built wi
train a simple convolutional neural network model on the MNIST dataset and prepare it for inference. train a simple convolutional neural network model on the MNIST dataset and prepare it for inference.
For clarity, we sometimes omit imports in our code snippets. For more details, please refer to the For clarity, we sometimes omit imports in our code snippets. For more details, please refer to the
corresponding code in the `examples/guide` [directory](https://github.com/tracel-ai/burn/tree/main/examples/guide). corresponding code in the `examples/guide` [directory](https://github.com/tracel-ai/burn/tree/release/0.14/examples/guide).
We reproduce this example in a step-by-step fashion, from dataset creation to modeling and training We reproduce this example in a step-by-step fashion, from dataset creation to modeling and training
in the following sections. It is recommended to use the capabilities of your IDE or text editor to in the following sections. It is recommended to use the capabilities of your IDE or text editor to
automatically add the missing imports as you add the code snippets to your code. automatically add the missing imports as you add the code snippets to your code.
@ -14,7 +14,8 @@ automatically add the missing imports as you add the code snippets to your code.
Be sure to checkout the git branch corresponding to the version of Burn you are using to follow Be sure to checkout the git branch corresponding to the version of Burn you are using to follow
this guide. this guide.
The current version of Burn is `0.14` and the corresponding branch to checkout is `main`. The current version of Burn is `0.14` and the corresponding branch to checkout is
[release/0.14](https://github.com/tracel-ai/burn/tree/release/0.14).
</div> </div>
The code for this demo can be executed from Burn's base directory using the command: The code for this demo can be executed from Burn's base directory using the command: