Instructions to use SidXXD/encoder_attack_4-eps-0628 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_attack_4-eps-0628 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-0628", 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:
- 0299461f9b30ac6b869bfe4ca140645bf77456656950694a2d979b734ac13e3e
- Size of remote file:
- 102 MB
- SHA256:
- a94ed5bbcac00e74562d998f9a7668a3464c3a0260720408a11b9453462336b7
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