Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionXLPipeline
sdxl
lora
dreambooth
photorealistic
Instructions to use Miggsoo3/MadelisVale-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Miggsoo3/MadelisVale-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("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Miggsoo3/MadelisVale-LoRA") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Madelis Vale LoRA v2 (SDXL Refined)
This LoRA is trained for photorealistic editorial portraits based on Stable Diffusion XL Base 1.0.
- Base model: stabilityai/stable-diffusion-xl-base-1.0
- LoRA weights:
Miggsoo3/MadelisVale-LoRA/pytorch_lora_weights.safetensors - Training: DreamBooth LoRA (SDXL, rank 16, fp16, ~10k steps)
🧩 Usage
Example Python snippet:
from diffusers import StableDiffusionXLPipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0"
)
pipe.load_lora_weights("Miggsoo3/MadelisVale-LoRA")
prompt = "a portrait photo of Madelis woman, cinematic lighting, ultra realistic skin"
image = pipe(prompt).images[0]
image.save("madelis_vale_output.png")
🖼️ Example
Coming soon: preview render from SDXL fine-tuned LoRA v2.
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Model tree for Miggsoo3/MadelisVale-LoRA
Base model
stabilityai/stable-diffusion-xl-base-1.0