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

- 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 XGGNet/lora-sdxl-szn LoRA adaption weights for stabilityai/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 man 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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Model tree for XGGNet/lora-sdxl-szn
Base model
stabilityai/stable-diffusion-xl-base-1.0