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A collection of various character loras (some of you may be familiar with my posts on [CivitAI](https://civitai.com/user/DocShotgun)) trained at 1024 resolution on [Pony Diffusion V6 XL](https://civitai.com/models/257749) and intended to be used with said model as well as derivative models such as [AutismMix SDXL](https://civitai.com/models/288584).
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These are trained using [DoRA](https://arxiv.org/abs/2402.09353) targetting the linear and conv layers of the unet while freezing the text encoder.
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Training was done using manually-gathered datasets and [Derrian Distro's training scripts](https://github.com/derrian-distro/LoRA_Easy_Training_Scripts) on 1x 4090. Detailed training data, including trained tags, is provided in the safetensors metadata included with each lora.
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A collection of various character loras (some of you may be familiar with my posts on [CivitAI](https://civitai.com/user/DocShotgun)) trained at 1024 resolution on [Pony Diffusion V6 XL](https://civitai.com/models/257749) and intended to be used with said model as well as derivative models such as [AutismMix SDXL](https://civitai.com/models/288584).
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These are trained using [DoRA](https://arxiv.org/abs/2402.09353) targetting the linear and conv layers of the unet while freezing the text encoder. All datasets were re-labeled and some were expanded with additional images to improve quality.
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Training was done using manually-gathered datasets and [Derrian Distro's training scripts](https://github.com/derrian-distro/LoRA_Easy_Training_Scripts) on 1x 4090. Detailed training data, including trained tags, is provided in the safetensors metadata included with each lora.
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