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Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 379 in Layer 1

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')



Text #0

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Max Act: 3.9171. Min Act: -0.1700

Data Index: 777748 (C4 (Web Text))

Max Activating Token Index: 866

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Text #1

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Max Act: 3.8546. Min Act: -0.1700

Data Index: 602726 (C4 (Web Text))

Max Activating Token Index: 265

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Text #2

Max Range: 3.9171. Min Range: -3.9171

Max Act: 3.8858. Min Act: -0.1700

Data Index: 1396131 (Python Code)

Max Activating Token Index: 701

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Text #3

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Max Act: 3.8546. Min Act: -0.1700

Data Index: 205532 (C4 (Web Text))

Max Activating Token Index: 534

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Text #4

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Max Act: 3.8546. Min Act: -0.1700

Data Index: 399603 (C4 (Web Text))

Max Activating Token Index: 696

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Text #5

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Data Index: 27736 (C4 (Web Text))

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Text #6

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Data Index: 913599 (C4 (Web Text))

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Text #7

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Data Index: 766102 (C4 (Web Text))

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Text #8

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Data Index: 462630 (C4 (Web Text))

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Text #9

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Data Index: 110824 (C4 (Web Text))

Max Activating Token Index: 49

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Text #10

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Data Index: 848180 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 1043309 (C4 (Web Text))

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Text #13

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Data Index: 422645 (C4 (Web Text))

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Text #14

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Text #15

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Text #16

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Data Index: 728667 (C4 (Web Text))

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Text #17

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Data Index: 1505333 (Python Code)

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Text #18

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Max Act: 3.6981. Min Act: -0.1700

Data Index: 10223 (C4 (Web Text))

Max Activating Token Index: 789

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Text #19

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Data Index: 493555 (C4 (Web Text))

Max Activating Token Index: 970

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