Instructions to use birdaz/mizuki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use birdaz/mizuki with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("birdaz/mizuki", 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 birdaz/mizuki: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/birdaz/mizuki/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://birdaz/mizuki@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/birdaz/mizuki/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 86e9dbef3f95c69d16d33c40211cbb75106dcd50de605c2a4d8a1fb9b6ffb13c
- Size of remote file:
- 246 MB
- SHA256:
- 5bd2f3ae3b3b1959e854374e0a0c1f77df6e4ccc7798c1ed641698596eb640f3
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