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End of training

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.gitattributes CHANGED
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+ image_0.png filter=lfs diff=lfs merge=lfs -text
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+ image_1.png filter=lfs diff=lfs merge=lfs -text
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+ image_2.png filter=lfs diff=lfs merge=lfs -text
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+ image_3.png filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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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: openrail++
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+ tags:
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+ - text-to-image
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+ - text-to-image
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+ - diffusers-training
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+ - diffusers
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+ - lora
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+ - template:sd-lora
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+ - stable-diffusion-xl
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+ - stable-diffusion-xl-diffusers
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+ instance_prompt: a photo of sks bear
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+ widget:
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+ - text: A superhero sks bear wearing red cape is flying through the sky
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+ output:
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+ url: image_0.png
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+ - text: A superhero sks bear wearing red cape is flying through the sky
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+ output:
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+ url: image_1.png
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+ - text: A superhero sks bear wearing red cape is flying through the sky
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+ output:
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+ url: image_2.png
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+ - text: A superhero sks bear wearing red cape is flying through the sky
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+ output:
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+ url: image_3.png
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+ ---
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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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+
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+
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+ # SDXL LoRA DreamBooth - ShuhongZheng/sdxl_bear_wo_preserve
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+
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+ <Gallery />
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+
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+ ## Model description
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+
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+ These are ShuhongZheng/sdxl_bear_wo_preserve LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/).
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+
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+ LoRA for the text encoder was enabled: False.
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+
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+ Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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+
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+ ## Trigger words
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+
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+ You should use a photo of sks bear to trigger the image generation.
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+
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+ ## Download model
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+
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+ Weights for this model are available in Safetensors format.
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+
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+ [Download](ShuhongZheng/sdxl_bear_wo_preserve/tree/main) them in the Files & versions tab.
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+
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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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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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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