A fine-tuned embedding model specialized for matching text to course content. It operates within a tight 512-token context window, so it works best with concise inputs like queries or short descriptions rather than long documents. Its narrow specialization means it likely excels at course-related semantic similarity tasks but may underperform on general-purpose embedding needs.