February 2025
Intermediate
376 pages
9h 25m
Japanese
Content preview from 仕組みからわかる大規模言語モデル 生成AI時代のソフトウェア開発入門
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1
トークンのサンプリング手法
1.5
1.2ではTransformer が入力されたトークンID の列から次のトークンID を予測し、選択さ
れたトークンID を現在の入力に追加しながら、終了トークンが生成されるまで応答メッセー
ジを生成する過程を説明しました。この過程では、確率分布を調整するためのパラメータを用
いることで、生成される応答メッセージの多様性や確定性を調整することができます。特に現
在主流のLLM では、次のパラメータがよく用いられます。
temperature
top-k
top-p
temperatureは、実質的にどのLLM でもサポートされているパラメータです。一方、top-k
とtop-p はそれぞれLLMが採用しているサンプリング手法に依存します。よく使われるサン
プリング手法としてtop-kサンプリングとtop-p サンプリング（nucleus sampling）があり、
それぞれtop-k と top-pが使用されます。
本節では、これらのパラメータがどのように使われるかについて説明します。
1.5.1
temperature
temperatureは、確率分布を調整するためのパラメータです。まずは、temperatureが確率
分布をどのように調整するかを確認した後、その計算を説明します。
確率分布の調整
temperatureに低い値を設定すると確率分布が尖り、確率の高いトークンが選択されやすく
なります。一方、temperature に高い値を設定すると ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.