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sanderland/science-sobotta-anatomical-drawings
science-sobotta-anatomical-drawings is a text-to-image model from sanderland. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
This is a Stable Diffusion model fine-tuned on the sbtstyle concept with DreamBooth. It can be used by modifying the instanceprompt: an anatomical drawing in the style of sbtstyle
Downloads · 30 days
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From the Hugging Face model README
This is a Stable Diffusion model fine-tuned on the sbtstyle concept with DreamBooth. It can be used by modifying the instance_prompt: an anatomical drawing in the style of sbtstyle
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Some more examples generated by others:
<table> <tr> <td> <img src="https://i.imgur.com/fOht9A9.jpg" style="max-height:300px"> </td> <td> <img src="https://i.imgur.com/GHCRf6n.png" style="max-height:300px"> </td> <td> </td> </tr> </table>The full dataset used to train on can be found here: Sanderbaduk/sobotta-anatomical-dataset.
These images and others like it can be found on wikimedia commons.
If you use this directly you will get an error as the raw images have different numbers of channels. Include a grayscale step to fix this and ensure that classic feel.
self.transforms = transforms.Compose(
[
transforms.Resize(size),
transforms.Grayscale(num_output_channels=3),
transforms.CenterCrop(size),
transforms.ToTensor(),
transforms.Normalize([0.5], [0.5]),
]
)
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Sanderbaduk/science-sobotta-anatomical-drawings')
image = pipeline().images[0]
image