Instructions to use gouthaml/raos-virtual-try-on-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gouthaml/raos-virtual-try-on-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gouthaml/raos-virtual-try-on-model", 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:
- 5b5c677b307665de2dd3eeb50d941672934ab0a5d8761d69ae54b9291ff43192
- Size of remote file:
- 2.13 GB
- SHA256:
- a47cf59409d600052231e2f17f4c694593ca7a876510b5cd9b737d2aba0bbd9e
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