Text-to-Image
Diffusers
TensorBoard
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
template:sd-lora
Instructions to use yleo/yannick_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yleo/yannick_LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/juggernaut-xl-v7", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yleo/yannick_LoRA") prompt = "<lora:yannick> man, beard" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
SDXL LoRA DreamBooth - yleo/yannick_LoRA
Model description
These are yleo/yannick_LoRA LoRA adaption weights for stablediffusionapi/juggernaut-xl-v7.
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 lora:yannick man, beard 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 yleo/yannick_LoRA
Base model
stablediffusionapi/juggernaut-xl-v7