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README.md
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---
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license: creativeml-openrail-m
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tags:
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- keras
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- diffusers
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- stable-diffusion
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- text-to-image
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- diffusion-models-class
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- dreambooth-hackathon
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- nature
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inference: true
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widget:
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- text: a photo of puggieace dog on the beach, sunset in background
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---
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# KerasCV Stable Diffusion in Diffusers 🧨🤗
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DreamBooth model for the `puggieace` concept trained by nielsgl on the `nielsgl/dreambooth-ace` dataset.
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It can be used by modifying the `instance_prompt`: **a photo of puggieace dog**
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## Description
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The pipeline contained in this repository was created using a modified version of [this Space](https://huggingface.co/spaces/sayakpaul/convert-kerascv-sd-diffusers) for StableDiffusionV2 from KerasCV. The purpose is to convert the KerasCV Stable Diffusion weights in a way that is compatible with [Diffusers](https://github.com/huggingface/diffusers). This allows users to fine-tune using KerasCV and use the fine-tuned weights in Diffusers taking advantage of its nifty features (like [schedulers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/schedulers), [fast attention](https://huggingface.co/docs/diffusers/optimization/fp16), etc.).
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This model was created as part of the Keras DreamBooth Sprint 🔥. Visit the [organisation page](https://huggingface.co/keras-dreambooth) for instructions on how to take part!
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## Examples
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> Portrait painting of a cute puggieace dog as a samurai
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> Photo of cute puggieace dog as an astronaut, space and planet in background
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> A photo of a cute puggieace dog getting a haircut in a barbershop
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> Portrait of puggieace dog as a Roman Emperor, city in background
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## Usage
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```python
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from diffusers import StableDiffusionPipeline
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pipeline = StableDiffusionPipeline.from_pretrained('nielsgl/dreambooth-keras-pug-ace-sd2.1')
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image = pipeline().images[0]
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image
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```
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