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AI’s

deployment

Prefix Tuning

A parameter-efficient fine-tuning method that prepends trainable continuous vectors (prefixes) to the input of each transformer layer. Only the prefix parameters are updated during training, leaving the original model weights frozen.

In practice

Prefix tuning adds trainable tokens to the beginning of each layer's input, steering model behavior without modifying core weights.