Instructions to use gz8iz/Wolfgang_Schmidt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gz8iz/Wolfgang_Schmidt 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("gz8iz/Wolfgang_Schmidt") prompt = "wsm bre in front of a green background, strong dramatic light, cinematic, highly detailed, built, intricate, very coherent, symmetry, great composition, illuminated, deep colors, inspired, rich vivid color, ambient romantic, beautiful scenic full detail, creative, perfect dynamic, peaceful atmosphere, artistic, positive, unique, awesome, elegant, cute, best, surreal, futuristic" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Wolfgang Schmidt

- Prompt
- wsm bre in front of a green background, strong dramatic light, cinematic, highly detailed, built, intricate, very coherent, symmetry, great composition, illuminated, deep colors, inspired, rich vivid color, ambient romantic, beautiful scenic full detail, creative, perfect dynamic, peaceful atmosphere, artistic, positive, unique, awesome, elegant, cute, best, surreal, futuristic
- Negative Prompt
- unrealistic, saturated, high contrast, big nose, painting, drawing, sketch, cartoon, anime, manga, render, CG, 3d, watermark, signature, label
Model description
just a LORA of Wolfgang Schmidt
Trigger words
You should use wsm to trigger the image generation.
You should use bre 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 gz8iz/Wolfgang_Schmidt
Base model
stabilityai/stable-diffusion-xl-base-1.0