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:
- 52839b090869e483be9d49805daefef94ab1c3a9e05bcf01ea30a4b01948cbd4
- Size of remote file:
- 687 kB
- SHA256:
- 880d37ba7ee3dbffee03e1ed3421e10eb493874fcfe0feeec3e535f53846e26a
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