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Constructing an SFT Training Pair for Text Summarization

A developer is creating a dataset to fine-tune a language model for text summarization. Below is a source text and the desired summary. Your task is to define the 'input sequence' and the 'output sequence' that would constitute a single training example for this Supervised Fine-Tuning task.

Source Text: "Quantum computing is an emerging field that harnesses the principles of quantum mechanics to solve problems too complex for classical computers. Unlike classical bits, which can be a 0 or a 1, quantum bits or 'qubits' can exist in a superposition of both states simultaneously. This property, along with entanglement, allows quantum computers to perform a vast number of calculations at once."

Desired Summary: "Quantum computing uses quantum mechanics principles like superposition and entanglement, allowing its 'qubits' to process vast calculations simultaneously, tackling problems beyond the reach of classical computers."

Based on the above, what would be the input sequence and the output sequence?

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Updated 2025-10-06

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Ch.4 Alignment - Foundations of Large Language Models

Foundations of Large Language Models

Foundations of Large Language Models Course

Computing Sciences

Ch.2 Generative Models - Foundations of Large Language Models

Application in Bloom's Taxonomy

Cognitive Psychology

Psychology

Social Science

Empirical Science

Science