Instructions to use siyich/ijd-unlearned-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use siyich/ijd-unlearned-checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("siyich/ijd-unlearned-checkpoints", 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
- Xet hash:
- 56c0b8f7b8ab4497fe0b96f66b1daf2bd96ead81b5079289d03e0237c695a12c
- Size of remote file:
- 344 MB
- SHA256:
- 44e8fc0fc8ada667b2303a5acbb259277c7d8312aae95bc54b272c9bb731e396
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