Instructions to use kaiyuyue/FLUX.2-dev-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kaiyuyue/FLUX.2-dev-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kaiyuyue/FLUX.2-dev-vae", 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
intro
fork the subdirectory black-forest-labs/FLUX.2-dev/vae to load only the VAE
usage
from diffusers.models import AutoencoderKL as DiffusersAutoencoderKL
model = DiffusersAutoencoderKL.from_pretrained("kaiyuyue/FLUX.2-dev-vae")
license
FLUX.2-dev LICENSE.md
- Downloads last month
- 1,409
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support