Instructions to use JasonYANG170/sd15-inpainting-onnx-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JasonYANG170/sd15-inpainting-onnx-fp32 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("JasonYANG170/sd15-inpainting-onnx-fp32", 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
Normalize ONNX pipeline metadata and PNDM scheduler
Browse files- SHA256SUMS +2 -2
- export-manifest.json +5 -5
- model_index.json +10 -11
- scheduler/scheduler_config.json +1 -6
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"_name_or_path": "C:\\Users\\qw200\\Documents\\ChatGPT\\eda-color\\model-exports\\.sd15-inpainting-onnx-fp32.source",
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