Instructions to use SidXXD/2_Attacked with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/2_Attacked 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/2_Attacked", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/2_Attacked: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/2_Attacked/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/2_Attacked/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/2_Attacked/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 32779c31f9c44ed4ceeefc3e313654f2c4908e276dc6bee6e0db95b79e80cbdc
- Size of remote file:
- 76.7 MB
- SHA256:
- 6b1e2a7b0b2900e78c09757a0b969d42dbae23a48855c34e9b85fa049cc97bdf
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