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
Download unet/diffusion_pytorch_model.bin from gouthaml/raos-virtual-try-on-model: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/gouthaml/raos-virtual-try-on-model/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://gouthaml/raos-virtual-try-on-model/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/gouthaml/raos-virtual-try-on-model/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 30046eebd98e0861b18e5ad53dd39b1fe0141342f4255af74e61d8e5fdf8f2c1
- Size of remote file:
- 3.44 GB
- SHA256:
- 04b9e60db98721ae5bab1019d10ca3d977f794a90f8e6b919ce51bdb89404859
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.