Instructions to use raw-vitor/danny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use raw-vitor/danny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("raw-vitor/danny", 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 raw-vitor/danny: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/raw-vitor/danny/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://raw-vitor/danny/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/raw-vitor/danny/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 17168b2bcc8c8b3969f38e875309bff1ffba51f301eb16f3f3ff379bce829c33
- Size of remote file:
- 3.44 GB
- SHA256:
- bb405d303b27b9b617bc3d0fad413021f3e7dd904b0a8c90e4399b5d80496b8d
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