Instructions to use EnD-Diffusers/oldvisual-kei-part-two with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/oldvisual-kei-part-two with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/oldvisual-kei-part-two", dtype=torch.bfloat16, device_map="cuda") prompt = "vskiy1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 02f28d73dd872e7b99686dc590df9e33541974d5687a57c0ad7a12e48ae44c25
- Size of remote file:
- 3.44 GB
- SHA256:
- 317127b9ac04c742c6452c48ac0de26e7d0f1090945e3aef7d5c3f57d678385a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.