Instructions to use AX1Y2JP/Krea-2-Raw-INT8-ConvRot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AX1Y2JP/Krea-2-Raw-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-Raw-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:
- 69b5bcf2141dc36034c205850cb4dd70c9612bffb4fbda74c01f1f2277a246ba
- Size of remote file:
- 16.2 GB
- SHA256:
- 47fa43cb3ae6937e26b0dd8c4dedd47cf0ba58f448407f443ff0915c3267f016
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