Instructions to use dx8152/Flux2-Klein-9B-Consistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dx8152/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("dx8152/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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
4b-base please or share dataset & settings
Hi really impressed in this lora for 9B. But I assume it doesn't work well for 4B that can be used commercially. Is there any chance to see see release for 4b-base or see "v2 dataset" and ai-toolkit settings? Thank you.
Hi really impressed in this lora for 9B. But I assume it doesn't work well for 4B that can be used commercially. Is there any chance to see see release for 4b-base or see "v2 dataset" and ai-toolkit settings? Thank you.
I've already broken down my training method and dataset in the video; you can try creating the same one: https://www.youtube.com/watch?v=j6dqOekUQ8c
Hi! Thank you for your work! How many “before and after” photo pairs did you use for training?
Hi! Thank you for your work! How many “before and after” photo pairs did you use for training?
150pair