Instructions to use tsolful/Krea2_Turbo_Raw_INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tsolful/Krea2_Turbo_Raw_INT8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tsolful/Krea2_Turbo_Raw_INT8", 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
25/06/2026 UPDATE - Uploaded the model that works with the new native implementation of INT8 in ComfyUI, for use with the native Load Diffusion Model node. Make sure you update your ComfyUI (Still works with the custom node but using native loads the model a bit faster for me)
INT8 ConvRot Quantization of the Krea 2 Turbo model
For use in ComfyUI with https://github.com/BobJohnson24/ComfyUI-INT8-Fast or any other INT8 Custom node
Krea 2 is licensed under the Krea 2 Community License Agreement. For more information, visit https://krea.ai/krea-2-licensing.
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