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Model: GELU Model: 4 Layers, 2048 Neurons per Layer

Dataset: 80% C4 (Web Text) and 20% Python Code

Neuron 27 in Layer 2

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

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Max Act: 4.1495. Min Act: -0.1700

Data Index: 1047887 (C4 (Web Text))

Max Activating Token Index: 844

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Text #1

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Data Index: 422499 (C4 (Web Text))

Max Activating Token Index: 416

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Text #2

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Max Act: 3.9932. Min Act: -0.1700

Data Index: 920221 (C4 (Web Text))

Max Activating Token Index: 930

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Text #3

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Data Index: 752512 (C4 (Web Text))

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Text #4

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Data Index: 231493 (C4 (Web Text))

Max Activating Token Index: 483

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Text #5

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Data Index: 1187114 (C4 (Web Text))

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Text #6

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Data Index: 485029 (C4 (Web Text))

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Text #7

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Data Index: 679637 (C4 (Web Text))

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Text #8

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Data Index: 368672 (C4 (Web Text))

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Text #9

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Data Index: 902911 (C4 (Web Text))

Max Activating Token Index: 385

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Text #10

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Data Index: 157674 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 1329883 (C4 (Web Text))

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Text #13

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Data Index: 658921 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 267333 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 161992 (C4 (Web Text))

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Text #18

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Data Index: 1103167 (C4 (Web Text))

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Text #19

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Data Index: 1119053 (C4 (Web Text))

Max Activating Token Index: 1006

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