Transformer Inference | How Inference is done in Transformer? | Deep Learning | CampusX
Inference in transformers involves generating predictions from the trained model. During inference, the decoder predicts one token at a time, using previously generated tokens and attending to the encoder's output. The process continues iteratively until the end of the sequence is reached, making it suitable for tasks like language translation and text generation.
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