Federated studying with differential privateness, i.e. non-public federated studying (PFL), makes it attainable to coach fashions on non-public knowledge distributed throughout customers’ gadgets with out harming privateness. PFL is environment friendly for fashions, akin to neural networks, which have a hard and fast variety of parameters, and thus a fixed-dimensional gradient vector. Such fashions embody neural-net language fashions, however not tokenizers, the subject of this work. Coaching a tokenizer…
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