Instructions to use ControlNet-1-1-preview/control_v11f1e_sd15_tile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ControlNet-1-1-preview/control_v11f1e_sd15_tile with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ControlNet-1-1-preview/control_v11f1e_sd15_tile") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
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README.md
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This checkpoint corresponds to the ControlNet conditioned on **tiled image**. Conceptually, it is similar to a super-resolution model, but its usage is not limited to that. It is also possible to generate details at the same size as the input (conditione) image.
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## Model Details
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- **Developed by:** Lvmin Zhang, Maneesh Agrawala
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- **Model type:** Diffusion-based text-to-image generation model
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This checkpoint corresponds to the ControlNet conditioned on **tiled image**. Conceptually, it is similar to a super-resolution model, but its usage is not limited to that. It is also possible to generate details at the same size as the input (conditione) image.
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**This model was contributed by [*takuma104*](https://huggingface.co/takuma104)**
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## Model Details
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- **Developed by:** Lvmin Zhang, Maneesh Agrawala
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- **Model type:** Diffusion-based text-to-image generation model
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