Instructions to use timbrooks/instruct-pix2pix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use timbrooks/instruct-pix2pix 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("timbrooks/instruct-pix2pix", 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
Commit ·
c0d6477
1
Parent(s): 11a8f3d
Adding `safetensors` variant of this model (#1)
Browse files
instruct-pix2pix-00-22000.safetensors
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safety_checker/model.safetensors
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version https://git-lfs.github.com/spec/v1
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text_encoder/model.safetensors
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unet/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fba63ff10c4271b953216b714c4f333c9d26d022e24ac226f09fde475812bd2a
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size 3438213622
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vae/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a2b5134f4dbc140d9c11f11cba3233099e00af40f262f136c691fb7d38d2194c
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size 334643276
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