Instructions to use tritueviet/Flux2-Klein-9B-Consistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tritueviet/Flux2-Klein-9B-Consistency 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("black-forest-labs/FLUX.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tritueviet/Flux2-Klein-9B-Consistency") 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
- Local Apps Settings
- Draw Things
- Xet hash:
- a9c8c9b1da0f7b8beb98f425cbdb773bea36b57db1548ba80ce09b07440d9e4a
- Size of remote file:
- 331 MB
- SHA256:
- 61db2017ce420b97bd5ef11984e5a894c90003a6bbf0dc9473f8d7b9ebb3ff93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.