Instructions to use AX1Y2JP/Krea-2-Turbo-INT8-ConvRot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AX1Y2JP/Krea-2-Turbo-INT8-ConvRot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AX1Y2JP/Krea-2-Turbo-INT8-ConvRot", 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:
- cd53adefe6bb6335ec639ccba99bcbf1b13719b1efd095ca4980441a211421ef
- Size of remote file:
- 603 kB
- SHA256:
- 1849942099ab15b6c7c4e6ae4cc22483d35eee7bceeeab57882c35fd62a93ce6
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