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Update README.md
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README.md
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- If you have low GPU RAM available, make sure to add a `pipe.enable_attention_slicing()` after sending it to `cuda` for less VRAM usage (to the cost of speed).
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## Available Checkpoints:
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## Training
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**Training Data**:
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- If you have low GPU RAM available, make sure to add a `pipe.enable_attention_slicing()` after sending it to `cuda` for less VRAM usage (to the cost of speed).
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## Available Checkpoints:
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- #### Stable:
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- [Sygil Diffusion v0.1](https://huggingface.co/Sygil/Sygil-Diffusion/blob/main/sygil-diffusion-v0.1.ckpt): Trained on Stable Diffusion 1.5 for 800,000 steps.
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- [Sygil Diffusion v0.2](https://huggingface.co/Sygil/Sygil-Diffusion/blob/main/sygil-diffusion-v0.2.ckpt): Resumed from Sygil Diffusion v0.1 and trained for a total of 1.77 million steps.
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- #### Beta:
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- [sygil-diffusion-v0.3_1860778_lora.ckpt](https://huggingface.co/Sygil/Sygil-Diffusion/blob/main/sygil-diffusion-v0.3_1860778_lora.ckpt): Resumed from Sygil Diffusion v0.2 and trained for a total of 1.86 million steps so far.
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Note: Checkpoints under the Beta section are updated daily or at least 3-4 times a week. This is usually the equivalent of 1-2 training session,
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this is done until they are stable enough to be moved into a proper release, usually every 1 or 2 weeks.
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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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is uploaded to keep the repo clean. The HuggingFace inference API as well as the diffusers library will always use the latest beta checkpoint in the diffusers format.
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For special cases we might make additional repositories to keep a copy of the diffusers model like when a model uses a different Stable Diffusion model as base (eg. Stable Diffusion 1.5 vs 2.1).
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## Training
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**Training Data**:
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