Instructions to use gz8iz/Volker_Wissing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gz8iz/Volker_Wissing 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/Volker_Wissing") prompt = "vwi bre in front of a green background, composition vivid, symmetry, stunning, highly detailed, professional, cinematic, saturated colors, intricate, elegant, incredible quality, light, crisp, extremely sharp detail, burning, beautiful, confident, epic, creative, positive, pure, attractive, artistic, loving, caring, cute, coherent, focused, best, full, pretty" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Volker Wissing

- Prompt
- vwi bre in front of a green background, composition vivid, symmetry, stunning, highly detailed, professional, cinematic, saturated colors, intricate, elegant, incredible quality, light, crisp, extremely sharp detail, burning, beautiful, confident, epic, creative, positive, pure, attractive, artistic, loving, caring, cute, coherent, focused, best, full, pretty
- 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 Volker Wissing
Trigger words
You should use vwi 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/Volker_Wissing
Base model
stabilityai/stable-diffusion-xl-base-1.0