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:
- d065bf8d882ddcf0c8019781c79c40a69e2029ac08ac0cf0221ca4853b477e6c
- Size of remote file:
- 5.36 GB
- SHA256:
- 7f250e98838e66a77be346ca669bce2580ac4df8ae353f96cf9a33b0c3c5c850
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