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--- |
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license: other |
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license_name: bespoke-lora-trained-license |
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license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False |
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tags: |
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- text-to-image |
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- stable-diffusion |
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- lora |
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- diffusers |
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- template:sd-lora |
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- migrated |
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- concept |
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- split |
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- split screen |
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- protoart |
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base_model: stabilityai/stable-diffusion-xl-base-1.0 |
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instance_prompt: 2splitstyle |
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widget: |
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- text: ' ' |
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output: |
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url: >- |
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24440943.jpeg |
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- text: ' ' |
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output: |
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url: >- |
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24429856.jpeg |
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- text: ' ' |
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output: |
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url: >- |
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24429858.jpeg |
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- text: ' ' |
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output: |
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url: >- |
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24429857.jpeg |
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--- |
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# Splitstyle 2.0 |
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<Gallery /> |
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## Model description |
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<p><span style="color:rgb(193, 194, 197)">Second attempt at creating a LoRa that recruits for different traditional art styles.</span></p><p></p><h3 id="i-would-recommend-having-the-cfg-scale-set-pretty-precise-and-the-step-counts-relatively-high-fwpakxmb0">I would recommend having the CFG scale set pretty precise, and the step counts relatively high</h3><p></p><p>I realized after the training was already completed. I trained us as a style and not a concept so this is the second attempt added a few more images to the data set up and that helps.</p><p>It should now allow you the option to create either two panels or four panel images. with the triggers "<strong>2splitstyle" or "4splitstyle"</strong></p><p><span style="color:rgb(193, 194, 197)">Trained on close-up portraits. Might take a bit more tinkering as it tends to just have two panels instead of four. anyway while i work out the bugs enjoy</span></p> |
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## Trigger words |
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You should use `2splitstyle`, `4splitstyle`, `splitstyle`, `split_style`, `evang` to trigger the image generation. |
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## Download model |
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Weights for this model are available in Safetensors format. |
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[Download](/brushpenbob/splitstyle-2-0/tree/main) them in the Files & versions tab. |
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
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```py |
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from diffusers import AutoPipelineForText2Image |
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import torch |
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pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda') |
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pipeline.load_lora_weights('brushpenbob/splitstyle-2-0', weight_name='Splitstyle_2.0.safetensors') |
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image = pipeline('`2splitstyle`, `4splitstyle`, `splitstyle`, `split_style`, `evang`').images[0] |
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``` |
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) |
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