This lecture explores decoding strategies in sequence-to-sequence models, covering deterministic methods like greedy decoding, exhaustive search, and beam search, as well as stochastic techniques like top-k sampling, nucleus sampling, and temperature sampling. It highlights the trade-offs between coherence, diversity, and computational efficiency in sequence generation.
🎓 Lecturer: Tanmoy Chakraborty [https://tanmoychak.com]
🔗 Get the Book: https://tanmoychak.com/llmbook
Discover key decoding strategies in sequence-to-sequence models, from deterministic methods like greedy decoding and beam search to stochastic techniques like top-k and nucleus sampling. This lecture explores the trade-offs between coherence, diversity, and computational efficiency in sequence generation.
