Instructions to use SidXXD/encoder_attack_4-eps-0157 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_attack_4-eps-0157 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/encoder_attack_4-eps-0157", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5083ebdc87dc1f51e6f55f17b9e00931bc9d83e9077c665144b23d28baf9f4d7
- Size of remote file:
- 102 MB
- SHA256:
- c8c9be72bfe00a0d0886f9d603ea3a2734efd34cb2fdc07a1af5b207a37621f9
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