Instructions to use gz8iz/Marco_Buschmann with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gz8iz/Marco_Buschmann 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/Marco_Buschmann") prompt = "mbu bre in front of a green background, sharp focus, highly detailed, cinematic, candid, intricate, elegant, confident, rich deep color, dramatic light, open atmosphere, inspired, designed, vivid, transparent, amazing detail, pretty, creative, epic, cool, awesome, winning, grand elaborate, trendy, best, romantic, hopeful, precious, colorful, rational" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Marco Buschmann

- Prompt
- mbu bre in front of a green background, sharp focus, highly detailed, cinematic, candid, intricate, elegant, confident, rich deep color, dramatic light, open atmosphere, inspired, designed, vivid, transparent, amazing detail, pretty, creative, epic, cool, awesome, winning, grand elaborate, trendy, best, romantic, hopeful, precious, colorful, rational
- 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 Marco Buschmann
Trigger words
You should use mbu 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/Marco_Buschmann
Base model
stabilityai/stable-diffusion-xl-base-1.0