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:
- 81012a349acee94a4c7108157a5f2e203fd33e6a6b207e7ca73548ff31ee4fd2
- Size of remote file:
- 3.44 GB
- SHA256:
- 59ea9abfbae4011cf9159623faf4122da83609b878f0dff2c1bad93fc3dfb9ad
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