Instructions to use mrdabin/poison with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mrdabin/poison with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mrdabin/poison", dtype=torch.bfloat16, device_map="cuda") 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
- Xet hash:
- 8784ce84f05015a5e3d186e2239e10a78c3312654395ff998938bde1fcf60aa0
- Size of remote file:
- 335 MB
- SHA256:
- 5d3ce45ab2dc4a923cd3f0aff597c5d37d77a891e1025783851547adeade8987
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.