Instructions to use Kartick/backstrap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kartick/backstrap with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kartick/backstrap", 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:
- 1c5ba1d5526ff0851e406dd4de1cf64f3b67a98d43bf180cbd4de4139d887f06
- Size of remote file:
- 246 MB
- SHA256:
- 3ee14f7d288a6fa3dec963e92b94697041221387d34d07c4548bb093c72c1159
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