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:
- 9361892792052b115591b2c6d3ba1fab2848935651dbbb3c4773eb02239e506a
- Size of remote file:
- 2.72 GB
- SHA256:
- ef6fdef70f98f9901ebbfadd6ba30fa60f33edabfd9c9cad49de8dfc17202a5a
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