Instructions to use Uminosachi/realisticVisionV51_v51VAE-inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Uminosachi/realisticVisionV51_v51VAE-inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Uminosachi/realisticVisionV51_v51VAE-inpainting", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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license: creativeml-openrail-m
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This is an inpainting model, which has been converted from the [realisticVisionV51_v51VAE-inpainting](https://civitai.com/models/4201?modelVersionId=130090).
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license: creativeml-openrail-m
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This is an inpainting model, which has been converted from the [realisticVisionV51_v51VAE-inpainting](https://civitai.com/models/4201?modelVersionId=130090).
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How to load the model :
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```python
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model_id = "sukkritsharma/realisticVisionV51_v51VAE-inpainting-onnx-fp16"
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pipe = OnnxStableDiffusionInpaintPipeline.from_pretrained(model_id,
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revision='fp16',
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provider="CUDAExecutionProvider",
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)
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```
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How to run inference :
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```python
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img = pipe(prompt=prompt,
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image=init_image,
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mask_image=mask_image,
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num_inference_steps=30).images[0]
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```
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