Instructions to use InstantX/InstantIR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/InstantIR 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("InstantX/InstantIR", 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:
- 41b654581ac38d63c0bc5e8e85cbcfa5ec0e628545e4705998c64335a21357f7
- Size of remote file:
- 4.02 GB
- SHA256:
- a6620aba5fbb9c19f4e251492cfffb85ffe05acf3b5bf4422b71ac4734c36897
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