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
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README.md
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# InstantIR restoration
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image = pipe(
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prompt='',
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image=image,
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ip_adapter_image=[image],
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negative_prompt='',
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guidance_scale=7.0,
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previewer_scheduler=lcm_scheduler,
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)[0]
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```
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For more details including text-guided enhancement/editing, please refer to our [GitHub repository](https://github.com/JY-Joy/InstantIR).
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# InstantIR restoration
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image = pipe(
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image=image,
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previewer_scheduler=lcm_scheduler,
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).images[0]
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```
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For more details including text-guided enhancement/editing, please refer to our [GitHub repository](https://github.com/JY-Joy/InstantIR).
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