nitrosocke
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Update README.md
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README.md
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@@ -7,11 +7,16 @@ Use the tokens **_arcane style_** in your prompts for the effect.
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If you enjoy this model, please check out my other models on [Huggingface](https://huggingface.co/nitrosocke)
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### Sample images from the model:
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![output Samples](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-output-images.jpg)
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### Sample images used for training:
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![Training Samples](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-training-images.jpg)
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**Version 2** (arcane-diffusion-v2): This uses the diffusers based dreambooth training and prior-preservation loss is way more effective. The diffusers where then converted with a script to a ckpt file in order to work with automatics repo.
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Training was done with 5k steps for a direct comparison to v1 and results show that it needs more steps for a more prominent result. Version 3 will be tested with 11k steps.
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If you enjoy this model, please check out my other models on [Huggingface](https://huggingface.co/nitrosocke)
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### Sample images from v3:
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![output Samples v3](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-v3-samples-01.jpg)
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![output Samples v3](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-v3-samples-02.jpg)
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### Sample images from the model:
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![output Samples](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-output-images.jpg)
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### Sample images used for training:
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![Training Samples](https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-training-images.jpg)
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**Version 3** (arcane-diffusion-v3): This version uses the new _train-text-encoder_ setting and improves the quality and edibility of the model immensely. Trained on 95 images from the show in 8000 steps.
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**Version 2** (arcane-diffusion-v2): This uses the diffusers based dreambooth training and prior-preservation loss is way more effective. The diffusers where then converted with a script to a ckpt file in order to work with automatics repo.
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Training was done with 5k steps for a direct comparison to v1 and results show that it needs more steps for a more prominent result. Version 3 will be tested with 11k steps.
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