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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バナナ:
0.2
(1/0.5)
=0.04
みかん:
0.1
(1/0.5)
=0.01
スケーリングされた確率分布は、次のように正規化されます。
りんご：
0.16/(0.16+0.09+0.04+0.01)=0.53
いちご：
0.09/(0.16+0.09+0.04+0.01)=0.30
バナナ：
0.04/(0.16+0.09+0.04+0.01)=0.13
みかん：
0.01/(0.16+0.09+0.04+0.01)=0.03
temperatureが 0.5 の場合、「りんご」が選ばれる可能性がさらに高くなります。つまり、低
いtemperature では、確率の高いトークンがさらに強調されます。
逆に、temperature の値が大きい場合も見てみましょう。2 の場合、確率分布は次のように
スケーリングされます。
りんご：
0.4
(1/2)
=0.63
いちご：
0.3
(1/2)
=0.55
バナナ：
0.2
(1/2)
=0.45
みかん：
0.1
(1/2)
=0.32
スケーリングされた確率分布は、次のように正規化されます。
りんご：
0.63/(0.63+0.55+0.45+0.32)=0.32
いちご：
0.55/(0.63+0.55+0.45+0.32)=0.28
バナナ：
0.45/(0.63+0.55+0.45+0.32)=0.23
みかん：
0.32/(0.63+0.55+0.45+0.32)=0.16
1.5.2
top-k（トップk）
top-kは、top-kサンプリング[Fan et al. ...
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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.
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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.