Instructions to use aggr8/PixEdit-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aggr8/PixEdit-v1 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("aggr8/PixEdit-v1", torch_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
Uploaded checkpoint!
Browse files- epoch_40_step_90041.pth +3 -0
epoch_40_step_90041.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:bdacc083dab13293833d76a4b6c36d0208f36955435b2962c5fb3e69f8fa2928
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size 4905931218
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