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license: cc0-1.0 |
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tags: |
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- art |
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--- |
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# Memleak.nude: a digital installation created through the nakedness of metal. |
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# Thesis and Methodology: |
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Humanity has switched intimacy and its entire realness into digital life, whereas public life has became a source of self-censorship. Our silicon collects it all, unfiltered, unlabeled and untethered by human boundaries. |
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The unfilteredness of data enticed me. Even though computers in the top levels have context about the data, like file headers, everything is clear and unfiltered binary when looked upon. |
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Therefore for 12 days, 20 minutes and 43 seconds before creating the dataset, the artist lived through their computer, never closing anything. allocated. garbage uncollected. |
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then, with aid from [ChatGpt](https://chatgpt.com/share/2d6be9f3-81fe-4e72-96ee-bf11bf052587) learned to dump all the memory into a raw data file, and a python script to convert the raw data to images. |
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The script generated 47365 images derived from my digital memory. This was a nude self portrait of my naked metal, my body without organs, the most sensitive data leak for a digital body. |
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The artist then curated 102 images out of this massive data to train this embedding. both as a way to keep their sensitive data safe and to be anonymously digitally naked. |
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The embedding was overtrained with a small learning rate to capture as many details from visualized raw data, 10000 steps and 1e-6. every third, the model was changed, sd 1.4, [analog diffusion](https://huggingface.co/wavymulder/Analog-Diffusion) and [retrodiffusion](https://www.retrodiffusion.ai/home) in the final pass. |
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the model and the embeddings are cc0, any outputs that come out can be commercialized by the output's creator, the end user, with no reference needed to me, the author. |
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have fun, do anything you like with it. i can't impose restrictions on beauty. |
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here are some of the raw outputs: |
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## Intended uses & limitations |
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create compositions out of an artist's most sensitive data leak. |
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#### How to use |
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copy the contents to your inversion embedding folders for your local stable diffusion. |
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#### Limitations and bias |
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the embedding works best at creating init images and be used in AND statements with a weight. i.e. a cat AND nakedMetal::0.ab . Personally found 0.17-0.4 the best range but you are invited to experiment if using. |
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## Training data |
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the training data consists of 102 images of the artist's personal sensitive raw data. here are a few examples: |
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