Instructions to use SidXXD/encoder_attack_4-eps-0620 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_attack_4-eps-0620 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-0620", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e7a64cf8bc2d4fd1b0a5d0592a0d138c394c25b4d61257ff211c15b22336ff7e
- Size of remote file:
- 102 MB
- SHA256:
- adc56a3a57cf73e3bf620d64db996f08fbb2644f56956061456bbf5a6b99a778
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