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--- |
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base_model: stabilityai/stable-diffusion-xl-base-1.0 |
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library_name: diffusers |
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license: creativeml-openrail-m |
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tags: |
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- stable-diffusion-xl |
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- stable-diffusion-xl-diffusers |
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- text-to-image |
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- diffusers |
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- diffusers-training |
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- lora |
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- stable-diffusion-xl |
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- stable-diffusion-xl-diffusers |
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- text-to-image |
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- diffusers |
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- diffusers-training |
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- lora |
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inference: true |
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widget: |
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- text: >- |
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pixel art cryptopunks, human, female, medium skin tone, Big Shades, Crazy |
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Hair |
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output: |
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url: images/example_ccse1jdid.png |
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- text: >- |
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pixel art cryptopunks, human, female, dark skin tone, Tassle Hat, Blue Eye |
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Shadow, Purple Lipstick, Earring |
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output: |
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url: images/example_e9bha5sos.png |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# LoRA text2image fine-tuning - SedatAl/Crypto-Punk-LoRa |
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the SedatAl/modified-cryptopunks dataset. You can find some example images in the following. |
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LoRA for the text encoder was enabled: False. |
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix. |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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[TODO: describe the data used to train the model] |
