Instructions to use Gemneye/K1mScum-ZImage-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gemneye/K1mScum-ZImage-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Gemneye/K1mScum-ZImage-Base") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Gemneye/K1mScum-ZImage-Base")
prompt = "-"
image = pipe(prompt).images[0]K1mScum-ZIB

- Prompt
- -
Model description
Z-Image-Base Model
Trigger words
You should use K1mScum to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for Gemneye/K1mScum-ZImage-Base
Base model
Tongyi-MAI/Z-Image