Instructions to use Benevolent/VeryBadImageNegative with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Benevolent/VeryBadImageNegative 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("Benevolent/VeryBadImageNegative") prompt = "UNICODE\u0000\u0000 \u0000r\u0000e\u0000f\u0000a\u0000m\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000f\u0000a\u0000m\u0000-\u0000l\u0000o\u0000r\u0000a\u0000-\u0000n\u0000o\u0000c\u0000h\u0000e\u0000k\u0000a\u0000i\u0000s\u0000e\u0000r\u0000:\u00001\u0000>\u0000,\u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
VBIN

- Prompt
- UNICODE refam, <lora:fam-lora-nochekaiser:1>,
Trigger words
You should use verybadimagenegative_v1.3 to trigger the image generation.
Download model
Weights for this model are available in PyTorch format.
Download them in the Files & versions tab.
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