Instructions to use QWW/EditCLIP-IP2P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QWW/EditCLIP-IP2P 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("QWW/EditCLIP-IP2P", 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
Upload image_proj_model.pt
Browse files- image_proj_model.pt +3 -0
image_proj_model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:94727660011fe9e7ccf53bfc32a94aa6f830c6d3570ec909515d3a9011e75ce9
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size 3157144
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