Sampling Methods in Practice: Temperature Scaling with Top-p/Top-k
~15 min read
Multinomial sampling picks from the probability distribution instead of always taking the top token — and in practice, it's almost never used alone. Temperature, top-p, and top-k are the three dials that shape the distribution being sampled from.
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Key points
- •Multinomial sampling picks from the probability distribution instead of always taking the top token — enables non-deterministic, varied output
- •Raw sampling from the unmodified distribution risks occasionally picking incoherent tokens from a long low-probability tail
- •Temperature, top-k, and top-p reshape or restrict the distribution BEFORE sampling — they're companions to sampling, not separate strategies
- •The common practical pattern: temperature ~0.7-0.9 combined with top-p ~0.9, not raw greedy and not raw unmodified sampling
- •This combination captures sampling's diversity benefit while avoiding its biggest risk — nonsensical tail tokens