Instructions to use bardakciisil/flux-img2img-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bardakciisil/flux-img2img-quantized 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("bardakciisil/flux-img2img-quantized", 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:
- 6eae279dc8f935c58908f7aee4d88f45b7f8323f7037c97c5a36467fe1e4bd52
- Size of remote file:
- 122 MB
- SHA256:
- 9535b0c145ef4664609f956e28eb34889f0ac86e1ae04613af7c07b0b038de09
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