Instructions to use ByteDance/XVerse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/XVerse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/XVerse", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 7be8bf4f0910f767db8e5226b41c493089bc0fd6c045a462345aa746f0588488
- Size of remote file:
- 1.81 GB
- SHA256:
- 9972a88c3bac19dbff770cbe1c3ad8ef791b1beb6eb9ab27c89ca106ac72f1ac
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