Text-to-Image
Diffusers
Safetensors
diffusion
nvfp4
awq
modelopt
quantized
krea2
blackwell
8-bit precision
Instructions to use sakamakismile/Krea-2-Turbo-NVFP4-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sakamakismile/Krea-2-Turbo-NVFP4-AWQ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sakamakismile/Krea-2-Turbo-NVFP4-AWQ", 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:
- 21a226c26428e4556dc1f2d63226e42d281c35240d495c94a6dd59687b5bb3bf
- Size of remote file:
- 2.93 MB
- SHA256:
- 951229ee326fe890cb7e9ecaec9ce862f5d6a9030b82ada4eb932eba98b062e2
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