Instructions to use koonoo/rovio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use koonoo/rovio with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("koonoo/rovio", 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 text_encoder/pytorch_model.bin from koonoo/rovio: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/koonoo/rovio/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://koonoo/rovio@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/koonoo/rovio/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 7caefad1b50c2a905764de6253369a1d5794e0244b730068b5972d640ffbeadf
- Size of remote file:
- 246 MB
- SHA256:
- 6a5c4f25d5bb49f9b07d2c9bd5c9e5d184f2f400b8198ead2f3d419887272dbc
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