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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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instance_prompt: an icon of trpfrog |
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widget: |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_0.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_1.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_2.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_3.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_4.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_5.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_6.png |
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- text: an icon of trpfrog eating ramen |
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output: |
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url: image_7.png |
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tags: |
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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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- 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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--- |
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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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# SDXL LoRA DreamBooth - Prgckwb/trpfrog-sdxl-lora |
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<Gallery /> |
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## Model description |
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These are Prgckwb/trpfrog-sdxl-lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. |
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The weights were trained using [DreamBooth](https://dreambooth.github.io/). |
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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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## Trigger words |
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You should use an icon of "trpfrog" to trigger the image generation. |
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## How to use |
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```python |
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from diffusers import DiffusionPipeline |
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import torch |
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base_model_id = 'stabilityai/stable-diffusion-xl-base-1.0' |
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lora_model_id = 'Prgckwb/trpfrog-sdxl-lora' |
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pipe = DiffusionPipeline.from_pretrained( |
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base_model_id, torch_dtype=torch.float16 |
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).to("cuda") |
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pipe.load_lora_weights(lora_model_id) |
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image = pipe( |
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"an icon of trpfrog", |
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num_inference_steps=25 |
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).images[0] |
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image.save('trpfrog.png') |
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``` |
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