The interesting part is findRunnable()—that’s where all the decisions happen. Let’s break down exactly how it searches for work.
"At that time, he wanted to become Dr Geisel at that point, not Dr. Seuss," Jones says.
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Врач раскрыла способ приучить кишечник работать по расписаниюВрач Гостроус: Три принципа питания помогают наладить работу кишечника
The predictor first projects the context embeddings from 768 down to 384 dimensions (a dimensional bottleneck). It then creates learnable “mask tokens” (placeholder vectors) for each masked position and concatenates them with the projected context embeddings. A 6-layer transformer processes this combined sequence, allowing the mask tokens to attend to the context tokens and gather the information they need. Finally, only the mask token outputs are extracted and projected back up to 768 dimensions for comparison with the target.
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