Instructions to use GraydientPlatformAPI/visionix-inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/visionix-inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/visionix-inpainting", 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:
- 5d6c9c8091d0723d8cb572fe6e2c1ca220bf2695594eb6d9d0517e4f13e8f98d
- Size of remote file:
- 1.39 GB
- SHA256:
- f07325d64321e0c27af97af6ea48e4748af412dd04e6bd27a9b8d2c24177cfd9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.