Instructions to use vladmandic/Krea-2-Base-sdnq-hadamard-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/Krea-2-Base-sdnq-hadamard-uint4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vladmandic/Krea-2-Base-sdnq-hadamard-uint4", 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:
- df4293400bceb59916783af9a77dcc100e15d7a45f5bedd89620f1eb6c5669a9
- Size of remote file:
- 7.75 GB
- SHA256:
- 7ced334339fd4d2a696198014486b95ad6da849101fe5d1273072903324d7357
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