Instructions to use mkshing/lora-sdxl-waterpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mkshing/lora-sdxl-waterpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mkshing/lora-sdxl-waterpainting") prompt = "a dog in szn style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
base_model: stable-diffusion-xl-base-1.0 instance_prompt: a cat of in szn style license: openrail++
SDXL LoRA DreamBooth - mkshing/lora-sdxl-waterpainting

- Prompt
- a dog in szn style

- Prompt
- a dog in szn style

- Prompt
- a dog in szn style

- Prompt
- a dog in szn style
Model description
These are mkshing/lora-sdxl-waterpainting LoRA adaption weights for /fsx/proj-jp-stable-diffusion/models/stable-diffusion/stable-diffusion-xl-base-1.0. The weights were trained using DreamBooth. LoRA for the text encoder was enabled: False. Special VAE used for training: None.
Trigger words
You should use a cat of in szn style to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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