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- {}
 
 
 
 
 
 
 
 
 
 
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  ---
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- ---
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- license: creativeml-openrail-m
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- tags:
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- - pytorch
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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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- - animal
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- widget:
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- - text: a photo of bongodog dog in the Acropolis
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- ---
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- # DreamBooth model for the bongodog concept trained by dacquaviva on the dacquaviva/bongodog dataset.
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- This is a Stable Diffusion model fine-tuned on the bongodog concept with DreamBooth. It can be used by modifying the `instance_prompt`: **a photo of bongodog dog**
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- This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!
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- ## Description
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-
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- This is a Stable Diffusion model fine-tuned on my `dog` images for the animal theme. His name is Bongo :).
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-
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- ## Usage
 
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- ```python
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- from diffusers import StableDiffusionPipeline
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-
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- pipeline = StableDiffusionPipeline.from_pretrained('dacquaviva/bongodog-dog')
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- image = pipeline().images[0]
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- image
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- ```
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-
 
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+ license: creativeml-openrail-m
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+ tags:
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+ - pytorch
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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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+ - animal
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+ widget:
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+ - text: a photo of bongodog dog in the Acropolis
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  ---
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+ # DreamBooth model for the bongodog concept trained by dacquaviva on the dacquaviva/bongodog dataset.
 
 
 
 
 
 
 
 
 
 
 
 
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+ This is a Stable Diffusion model fine-tuned on the bongodog concept with DreamBooth. It can be used by modifying the `instance_prompt`: **a photo of bongodog dog**
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+ This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!
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+ ## Description
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+ This is a Stable Diffusion model fine-tuned on my `dog` images for the animal theme. His name is Bongo :).
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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('dacquaviva/bongodog-dog')
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+ image = pipeline().images[0]
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+ image
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+ ```