Instructions to use not-pegasus/IMAGE_MODAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use not-pegasus/IMAGE_MODAL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("not-pegasus/IMAGE_MODAL", 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:
- f14d5564a92fa11fdb9ccb12c6804c843476c0923f0e04fc2c36b20a8ffdc7f6
- Size of remote file:
- 6.89 MB
- SHA256:
- 921d6dc8134821fd0d168885ddd33f3e5d23b75a1391e4fc526da43e7fb6ada5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.