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license: mit
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It can be used by modifying the `instance_prompt`: **a photo of sks zach fox**
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You can also train your own concepts and upload them to the library by using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_training.ipynb).
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And you can run your new concept via `diffusers`: [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb), [Spaces with the Public Concepts loaded](https://huggingface.co/spaces/sd-dreambooth-library/stable-diffusion-dreambooth-concepts)
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Here are the images used for training this concept:
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license: mit
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language: en
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tags:
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- text-to-image
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# Zach Fox Stable Diffusion
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Stable Diffusion v1.5 model fine-tuned to generate pictures of Zach Fox with Dreambooth.
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It can be used by modifying the `instance_prompt`: **a photo of sks zach fox**
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You can also train your own concepts and upload them to the library by using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_training.ipynb).
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And you can run your new concept via `diffusers`: [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb), [Spaces with the Public Concepts loaded](https://huggingface.co/spaces/sd-dreambooth-library/stable-diffusion-dreambooth-concepts)
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## Usage
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To use this model, you can run the following...
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```python
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import torch
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from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained("nateraw/zach-fox", torch_dtype=torch.float16).to("cuda")
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prompt = "a photo of sks zach fox, oil on canvas"
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image = pipe(prompt).images[0]
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```
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Here are the images used for training this concept:
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