Instructions to use krnl/venereital-IA-23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krnl/venereital-IA-23 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krnl/venereital-IA-23", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3aa2f576d0bc59d1f21139a794716299dda4bbc17af682e9681717a201c169e5
- Size of remote file:
- 1.36 GB
- SHA256:
- 7e5c00c5e6ade0db4d9f8e0432d7118ddac85684bd2035e7c715a1edadcc32e3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.