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Model: GELU Model: 1 Layers, 2048 Neurons per Layer

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

Neuron 2016 in Layer 0

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Hooked Transformer Loading: HookedTransformer.from_pretrained('gelu-1l')

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Text #0

Max Range: 3.7572. Min Range: -3.7572

Max Act: 3.7572. Min Act: -0.1700

Data Index: 371130 (C4 (Web Text))

Max Activating Token Index: 800

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Text #1

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Max Act: 3.7438. Min Act: -0.1700

Data Index: 1362011 (Python Code)

Max Activating Token Index: 722

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Text #2

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Max Act: 3.7274. Min Act: -0.1700

Data Index: 385020 (C4 (Web Text))

Max Activating Token Index: 972

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Text #3

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Max Act: 3.7212. Min Act: -0.1700

Data Index: 641351 (C4 (Web Text))

Max Activating Token Index: 817

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Text #4

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Max Act: 3.6956. Min Act: -0.1700

Data Index: 628132 (C4 (Web Text))

Max Activating Token Index: 274

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Text #5

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Max Act: 3.6920. Min Act: -0.1700

Data Index: 1253971 (C4 (Web Text))

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Text #6

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Data Index: 564244 (C4 (Web Text))

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Text #7

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Data Index: 400085 (C4 (Web Text))

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Text #8

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Data Index: 535986 (C4 (Web Text))

Max Activating Token Index: 799

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Text #9

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Data Index: 1462302 (Python Code)

Max Activating Token Index: 265

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Text #10

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Data Index: 1136030 (C4 (Web Text))

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Text #11

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Data Index: 513739 (C4 (Web Text))

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Text #12

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Data Index: 312715 (C4 (Web Text))

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Text #13

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Data Index: 191075 (C4 (Web Text))

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Text #14

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Data Index: 406317 (C4 (Web Text))

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Text #15

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Data Index: 1229563 (C4 (Web Text))

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Text #16

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Data Index: 1408251 (Python Code)

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Text #17

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Data Index: 1585991 (Python Code)

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Text #18

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Data Index: 1635465 (Python Code)

Max Activating Token Index: 725

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Text #19

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Data Index: 1623718 (Python Code)

Max Activating Token Index: 633

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