--- base_model: stabilityai/stable-diffusion-xl-base-1.0 library_name: diffusers license: openrail++ widget: - text: anime rat in a jungle output: url: images/example_xj9kri2rp.png - text: photorealistic cat in a jungle output: url: images/example_0aal2cjg1.png tags: - text-to-image - text-to-image - diffusers-training - diffusers - lora - template:sd-lora - stable-diffusion-xl - stable-diffusion-xl-diffusers --- # SDXL LoRA DreamBooth - ariG23498/open-image-preferences-v1-sdxl-lora ## Comparison | Prompt | SDXL | Fine Tuned | | :--: | :--: | :--: | | a boat in the canals of Venice, painted in gouache with soft, flowing brushstrokes and vibrant, translucent colors, capturing the serene reflection on the water under a misty ambiance, with rich textures and a dynamic perspective | ![image/png](https://cdn-uploads.huggingface.co/production/uploads/608aabf24955d2bfc3cd99c6/CtoZWxDmANYm7d95I3Fcp.png) | ![image/png](https://cdn-uploads.huggingface.co/production/uploads/608aabf24955d2bfc3cd99c6/hAxmaL-robradk1x_KqwQ.png) | | Grainy shot of a robot cooking in the kitchen, with soft shadows and nostalgic film texture. | ![image/png](https://cdn-uploads.huggingface.co/production/uploads/608aabf24955d2bfc3cd99c6/LTQI1NdaEjJUgeDpqzv7k.png) | ![image/png](https://cdn-uploads.huggingface.co/production/uploads/608aabf24955d2bfc3cd99c6/vAjnMCW0nmbV0zHKT8oCJ.png) | ## Model description These are ariG23498/open-image-preferences-v1-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: None. ## Trigger words You should use None to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](ariG23498/open-image-preferences-v1-sdxl-lora/tree/main) them in the Files & versions tab. ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]