Instructions to use feishen29/IMAGDressing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use feishen29/IMAGDressing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("feishen29/IMAGDressing", 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:
- 80d575bba599101d86214de356558e52e95d5d57847d8fcb018aa06019a68d4d
- Size of remote file:
- 289 MB
- SHA256:
- 80ffe37d8a5940d59a7384c201a2a38d4741f2f3c51eef46ebb28218a7b0ca2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.