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README.md
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- mixed_precision_training: Apex, opt level O1
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## How to use
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Before being able to use this model, it is necessary to clone and configure the [codebase](https://github.com/xplip/pixel)
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*Instructions from [https://github.com/xplip/pixel](https://github.com/xplip/pixel)*
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### Setup
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This codebase is built on [Transformers](https://github.com/huggingface/transformers) for PyTorch. We also took inspiration from the original [ViT-MAE codebase](https://github.com/facebookresearch/mae). The default font `GoNotoCurrent.ttf` that we used for all experiments is a merged Noto font built with [go-noto-universal](https://github.com/satbyy/go-noto-universal).
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- mixed_precision_training: Apex, opt level O1
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## How to use
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+
Before being able to use this model, it is necessary to clone and configure the [codebase](https://github.com/xplip/pixel).
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### Setup
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+
*Instructions from [https://github.com/xplip/pixel](https://github.com/xplip/pixel)*
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This codebase is built on [Transformers](https://github.com/huggingface/transformers) for PyTorch. We also took inspiration from the original [ViT-MAE codebase](https://github.com/facebookresearch/mae). The default font `GoNotoCurrent.ttf` that we used for all experiments is a merged Noto font built with [go-noto-universal](https://github.com/satbyy/go-noto-universal).
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