Instructions to use onkarsus13/controlnet_stablediffusion_scenetextEraser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use onkarsus13/controlnet_stablediffusion_scenetextEraser 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("onkarsus13/controlnet_stablediffusion_scenetextEraser", 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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license: mit
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This is the trained model for the controlnet-stablediffusion for the scene text eraser (Diff_SceneTextEraser)
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We have to customize the pipeline for
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For direct inference
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license: mit
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---
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This is the trained model for the controlnet-stablediffusion for the scene text eraser (Diff_SceneTextEraser)
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We have to customize the pipeline for controlnet-stablediffusion-inpaint
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Here is the training and inference code for [Diff_SceneTextEraser](https://github.com/Onkarsus13/Diff_SceneTextEraser)
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For direct inference
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