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Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models.In this task, a generative model that was trained on large-scale data (usually a foundation model), is adapted such that it can generate images of novel, user-provided concepts.
The sentence "The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents", in Zalgo textZalgo text is generated by excessively adding various diacritical marks in the form of Unicode combining characters to the letters in a string of digital text. [4]
In 2016, Reed, Akata, Yan et al. became the first to use generative adversarial networks for the text-to-image task. [5] [7] With models trained on narrow, domain-specific datasets, they were able to generate "visually plausible" images of birds and flowers from text captions like "an all black bird with a distinct thick, rounded bill".
Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the ...
Dissociated press is a parody generator (a computer program that generates nonsensical text). The generated text is based on another text using the Markov chain technique. The name is a play on "Associated Press" and the psychological term dissociation (although word salad is more typical of conditions like aphasia and schizophrenia – which is, however, frequently confused with dissociative ...
Sharing is also much easier—gone are the days of typing up your notes after a call, with tablets you can simply export a PDF, auto-convert to typed text, or send quick screenshots. ReMarkable
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