Instructions to use codeShare/FLUX.2-klein-9b-SDNQ-2bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/FLUX.2-klein-9b-SDNQ-2bit 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/FLUX.2-klein-9b-SDNQ-2bit", 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:
- 700b5a43e8e1d7ce68f55a6a6f8c942a10d99f1777ad5eca80ad380ace7c4846
- Size of remote file:
- 1.65 GB
- SHA256:
- fba06c5b2d0a3ae32aa89554ca4decbcf53c037bcbfafd137138719e7885c9f1
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