Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
template:sd-lora
Instructions to use kpal002/Dreambooth-SDXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kpal002/Dreambooth-SDXL 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("kpal002/Dreambooth-SDXL") prompt = "A portrait in a distinctive expressive style characterized by vivid color use, emotional depth, and dynamic brush strokes, capturing the nuanced expressions of children and teenagers." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
AutoTrain SDXL LoRA DreamBooth - kpal002/Dreambooth-SDXL
Model description
These are kpal002/Dreambooth-SDXL 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 portrait in a distinctive expressive style characterized by vivid color use, emotional depth, and dynamic brush strokes, capturing the nuanced expressions of children and teenagers. 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 kpal002/Dreambooth-SDXL
Base model
stabilityai/stable-diffusion-xl-base-1.0