Instructions to use gleebergoob/abcumshot3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gleebergoob/abcumshot3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("amsas10/fasfas", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("gleebergoob/abcumshot3") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/IMG_2989.jpg
base_model: amsas10/fasfas
instance_prompt: null
license: wtfpl
fasf

- Prompt
- -
Model description
fasf
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.