Instructions to use Video-Reason/VBVR-Pro-FLUX2-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Video-Reason/VBVR-Pro-FLUX2-dev 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("Video-Reason/VBVR-Pro-FLUX2-dev", 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
- Xet hash:
- ed94c8e9960547c3d72b82d3985b0f63c47c3a1a70690e74581ce34325bcade4
- Size of remote file:
- 9.89 GB
- SHA256:
- d9b1972938a5cb93aa502859e1d660767b9bb4786b31385287596f67e2d687f6
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