Text-to-Image
Diffusers
Safetensors
English
Krea2Pipeline
krea2
sdnq
uint4
4-bit precision
quantized
8-bit precision
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:
- 28e587d970d27de495ab1f2c06c58292d7fff5970dce390c7f78d0b8259e4537
- Size of remote file:
- 4.98 GB
- SHA256:
- 163e344e665310e99bf45c2b6e748bae8216b097d626c8758188444246e63e9b
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