Instructions to use taraxis/shishav1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use taraxis/shishav1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("taraxis/shishav1", dtype=torch.bfloat16, device_map="cuda") prompt = "shsatst" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 320db007ee92799768121603c9704f210aa52288bd6a419798525d0ff0ede738
- Size of remote file:
- 492 MB
- SHA256:
- 85b21850ecf3d4843c0151f442cd5140378a9ba40409458a6a38a836fcbcb2e6
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