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Update README.md
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README.md
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@@ -40,7 +40,7 @@ This model is still in its infancy and it's meant to be constantly updated and t
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- #### Stable:
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- No stable version available right now.
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- #### Beta:
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- [vae.
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- [maskgit.1206000.p](https://huggingface.co/Sygil/Sygil-Muse/blob/main/maskgit.1206000.pt): Maskgit trained from the VAE for 1.20M steps
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Note: Checkpoints under the Beta section are updated daily or at least 3-4 times a week. While the beta checkpoints can be used as they are only the latest version is kept on the repo and the older checkpoints are removed when a new one
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- **Resolution/Image Size**: First trained at a resolution of 64x64, then increased to 256x256 and then to 512x512. Check the notes down below for more details on this.
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- **Dimension:** 128
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- **vq_codebook_size:** 256
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- **Total Training Steps:** 2,
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Note: On Muse we can change the image_size or resolution at any time without having to train the model from scratch again, this allows us to first train the model at low resolution using the same `dim` and `vq_codebook_size` to train faster and then we can increase the `image_size` and use a higher resolution once the model has trained enough.
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- #### Stable:
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- No stable version available right now.
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- #### Beta:
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- [vae.2771500.pt](https://huggingface.co/Sygil/Sygil-Muse/blob/main/vae.2771500.pt): Trained from scratch for 2.77M steps
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- [maskgit.1206000.p](https://huggingface.co/Sygil/Sygil-Muse/blob/main/maskgit.1206000.pt): Maskgit trained from the VAE for 1.20M steps
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Note: Checkpoints under the Beta section are updated daily or at least 3-4 times a week. While the beta checkpoints can be used as they are only the latest version is kept on the repo and the older checkpoints are removed when a new one
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- **Resolution/Image Size**: First trained at a resolution of 64x64, then increased to 256x256 and then to 512x512. Check the notes down below for more details on this.
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- **Dimension:** 128
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- **vq_codebook_size:** 256
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- **Total Training Steps:** 2,771,500
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Note: On Muse we can change the image_size or resolution at any time without having to train the model from scratch again, this allows us to first train the model at low resolution using the same `dim` and `vq_codebook_size` to train faster and then we can increase the `image_size` and use a higher resolution once the model has trained enough.
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