Text-to-Image
Diffusers
Safetensors
English
Krea2Pipeline
krea2
sdnq
uint4
4-bit precision
quantized
Instructions to use WaveCut/Krea-2-Raw-SDNQ-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Krea-2-Raw-SDNQ-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("WaveCut/Krea-2-Raw-SDNQ-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:
- 7c9b35674910b5a25a940ef1cae9e49d27dd384d5f44ba0e2fae08ab06ed5d7a
- Size of remote file:
- 3.74 MB
- SHA256:
- aee71f25554db6ca841e9b28315825e4ab6132e5d362e5eeffb2ecb6ca93ac1e
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