Instructions to use SidXXD/encoder_attack_2-eps-0078 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_attack_2-eps-0078 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_2-eps-0078", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7955fd90d8bec1d9dc1c2627160bf2c76b5dee512da7747fc935026df0e07441
- Size of remote file:
- 102 MB
- SHA256:
- 98f745622b0bf8726aa69ab377b560c4ed602fc715f250b4e2bbffed64278b15
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