Instructions to use duja1/roy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/roy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/roy", dtype=torch.bfloat16, device_map="cuda") prompt = "r123oy" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from duja1/roy: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/duja1/roy/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://duja1/roy/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/duja1/roy/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- d25b34a4049f9a821800421d923b0a7de01d88123d5c418cc3fc5a0ef60ff748
- Size of remote file:
- 3.44 GB
- SHA256:
- 694a7d29302e551214719d77b7d3cde8b464459e3026c11cf599172faa86b726
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