Instructions to use ShadoWxShinigamI/mjstyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShadoWxShinigamI/mjstyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShadoWxShinigamI/mjstyle", 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
- Draw Things
- DiffusionBee
- Xet hash:
- f99bf37b61d5eec0a55f611ce4dbf3a92f7ec5981c01bbc5e62e7112f2efbab0
- Size of remote file:
- 2.13 GB
- SHA256:
- d1004a4e24b65313730d1da148dc5e5d98bf93ffb5efb3e314a33abb2573b796
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