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:
- 304188cf652d0e942c7f9cbb45e2fba106e32230474957b2bb896ead1612fc69
- Size of remote file:
- 5.04 MB
- SHA256:
- cc27a9c5c5ea41785bffd3c0142a83ca87881aeda3604c5052f5eccd5602f5fc
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