Instructions to use openvivo/BluePixel-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openvivo/BluePixel-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openvivo/BluePixel-Turbo", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Inquiry: License tag discrepancy (Apache-2.0 vs FLUX Non-Commercial)
Hello Vivo team,
First of all, thank you for open-sourcing BluePixel-Turbo and your great contribution to the community!
I am writing to gently point out a potential licensing compliance issue that might inadvertently mislead users. The model card mentions that this model builds on FLUX.2-klein-9B, which is released under the FLUX Non-Commercial License. However, the repository is tagged with the Apache-2.0 license.
Because the base 9B model is restricted to non-commercial use, displaying the Apache-2.0 tag might cause developers to mistakenly use this model for commercial purposes, leading to unintended license violations with Black Forest Labs.
Could you please double-check the license tag or add a clarification note in the model card? This would greatly help the community avoid potential legal risks.

