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:
- 2c3d588e8d297fff18cd71b5ab85b6ab0c3d5817f0cc979828e922b047e83864
- Size of remote file:
- 3.06 GB
- SHA256:
- 5911bfcd683f68abb68bcdbdf90889aff4c98f163652627c1a1bebd8d30ecf3c
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