--- base_model: stabilityai/stable-diffusion-xl-base-1.0 library_name: diffusers license: openrail++ instance_prompt: an icon of trpfrog widget: - text: an icon of trpfrog eating ramen output: url: image_0.png - text: an icon of trpfrog eating ramen output: url: image_1.png - text: an icon of trpfrog eating ramen output: url: image_2.png - text: an icon of trpfrog eating ramen output: url: image_3.png - text: an icon of trpfrog eating ramen output: url: image_4.png - text: an icon of trpfrog eating ramen output: url: image_5.png - text: an icon of trpfrog eating ramen output: url: image_6.png - text: an icon of trpfrog eating ramen output: url: image_7.png tags: - text-to-image - diffusers-training - diffusers - lora - template:sd-lora - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - text-to-image - diffusers-training - diffusers - lora - template:sd-lora - stable-diffusion-xl - stable-diffusion-xl-diffusers --- # SDXL LoRA DreamBooth - Prgckwb/trpfrog-sdxl-lora ## Model description These are Prgckwb/trpfrog-sdxl-lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained using [DreamBooth](https://dreambooth.github.io/). LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix. ## Trigger words You should use an icon of "trpfrog" to trigger the image generation. ## How to use ```python from diffusers import DiffusionPipeline import torch base_model_id = 'stabilityai/stable-diffusion-xl-base-1.0' lora_model_id = 'Prgckwb/trpfrog-sdxl-lora' pipe = DiffusionPipeline.from_pretrained( base_model_id, torch_dtype=torch.float16 ).to("cuda") pipe.load_lora_weights(lora_model_id) image = pipe( "an icon of trpfrog", num_inference_steps=25 ).images[0] image.save('trpfrog.png') ```