Instructions to use codeShare/Flux2Klein_AIO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/Flux2Klein_AIO 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("codeShare/Flux2Klein_AIO", 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
Rename transformer/aio_diffusion_model_flux_klein_4b_fp16.safetensors to transformer/diffusion_pytorch_model.safetensors
Browse files
transformer/{aio_diffusion_model_flux_klein_4b_fp16.safetensors → diffusion_pytorch_model.safetensors}
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