Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
Instructions to use SidXXD/encoder_attack-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_attack-1 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-1", 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
Ctrl+K
- 1719324001.7120986
- 1719324001.7137432
- 1719935555.3206806
- 1719935555.3223946
- 1719935607.5738544
- 1719935607.5758965
- 1719935810.597708
- 1719935810.59952
- 1719936964.962563
- 1719936964.9645748
- 1719937933.4063876
- 1719937933.4082248
- 1719938040.8306978
- 1719938040.8324723
- 1719938200.8120234
- 1719938200.8137348
- 1719939153.7130437
- 1719939153.7150965
- 1719939271.4262435
- 1719939271.4281807
- 1719939373.118812
- 1719939373.120894
- 1719939568.1306415
- 1719939568.1329355
- 1719940533.2718072
- 1719940533.2736197
- 20.8 kB xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 88 Bytes xet
- 21 kB xet
- 21 kB xet