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README.md
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---
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license: mit
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library_name: pytorch
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tags:
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- image-generation
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- gan
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- stylegan
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- stylegan3
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- nvidia
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---
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# Anime Faces Generator (StyleGAN3 by NVIDIA)
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<img width="679" alt="Generated Faces" src="https://user-images.githubusercontent.com/35907066/161809457-e6467724-5942-4a89-b379-85ddfd6ac86c.png">
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This is a [StyleGAN3 PyTorch](https://github.com/NVlabs/stylegan3) model trained on this [Anime Face Dataset](https://github.com/bchao1/Anime-Face-Dataset).
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### Usage
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Demo on Spaces is not yet implemented.
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You can run the model pickle file locally using the instructions in this generator-script-only subset of the StyleGAN3 repo:
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- https://github.com/venture-anime/stylegan3-anime-faces-generator
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### Dataset & Model Details
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The [Anime Face Dataset](https://github.com/bchao1/Anime-Face-Dataset) was created by Mckinsey666.
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Training was done in [Paperspace Gradient](https://gradient.run/) on a free `RTX-5000` instance with the following parameters:
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- Configuration: `stylegan3-t`
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- GPUs: `1`
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- Batch Size: `8`
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- Gamma: `0.5`
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- Final tick: `102`
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- Final
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# Train your own StyleGAN3 on PaperSpace or Colab
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You can use the notebooks here for a ready-to-use training pipeline
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https://github.com/akiyamasho/stylegan3-training-notebook
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---
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license: mit
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library_name: pytorch
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tags:
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- image-generation
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- gan
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- stylegan
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- stylegan3
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- nvidia
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---
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# Anime Faces Generator (StyleGAN3 by NVIDIA)
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<img width="679" alt="Generated Faces" src="https://user-images.githubusercontent.com/35907066/161809457-e6467724-5942-4a89-b379-85ddfd6ac86c.png">
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This is a [StyleGAN3 PyTorch](https://github.com/NVlabs/stylegan3) model trained on this [Anime Face Dataset](https://github.com/bchao1/Anime-Face-Dataset).
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### Usage
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+
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Demo on Spaces is not yet implemented.
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+
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You can run the model pickle file locally using the instructions in this generator-script-only subset of the StyleGAN3 repo:
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- https://github.com/venture-anime/stylegan3-anime-faces-generator
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### Dataset & Model Details
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The [Anime Face Dataset](https://github.com/bchao1/Anime-Face-Dataset) was created by Mckinsey666.
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Training was done in [Paperspace Gradient](https://gradient.run/) on a free `RTX-5000` instance with the following parameters:
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- Configuration: `stylegan3-t`
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- GPUs: `1`
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- Batch Size: `8`
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- Gamma: `0.5`
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- Final tick: `102`
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- Final fid50k_full value (this pickle): `9.26043547642206`.
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# Train your own StyleGAN3 on PaperSpace or Colab
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+
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You can use the notebooks here for a ready-to-use training pipeline
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https://github.com/akiyamasho/stylegan3-training-notebook
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