Instructions to use Mariobilly/flat-vector-shapes-000003000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mariobilly/flat-vector-shapes-000003000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Mariobilly/flat-vector-shapes-000003000") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
license: other
library_name: diffusers
pipeline_tag: text-to-image
tags:
- lora
- z-image
- z-image-turbo
- text-to-image
Flat vector shapes 000003000
LoRA for Z-Image Turbo.
- File:
Flat vector shapes_000003000.safetensors - Trigger word:
flatvectorshapes - Trained by: @Mariobilly
Samples
Usage
Place the .safetensors file in your models/loras/ folder and load it
in ComfyUI or your inference UI of choice. Include the trigger word flatvectorshapes
in your prompt to activate the LoRA.
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo")
pipe.load_lora_weights("Mariobilly/flat-vector-shapes-000003000")
image = pipe("flatvectorshapes, your prompt here").images[0]



