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:
- 5d6e8c96b530b2454bc3d67eb70bb3215978577f330d505c9d292157fc3383f2
- Size of remote file:
- 2.13 GB
- SHA256:
- 3de471925680bfb13eeff292fecf1b2c103afd72f4611f785e118e109f19eaf7
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