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

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

Neuron 120 in Layer 3

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: 4.6125. Min Act: -0.1700

Data Index: 770164 (C4 (Web Text))

Max Activating Token Index: 25

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Text #1

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Data Index: 144251 (C4 (Web Text))

Max Activating Token Index: 21

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Text #2

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Data Index: 656700 (C4 (Web Text))

Max Activating Token Index: 24

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Text #3

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Data Index: 665905 (C4 (Web Text))

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Text #4

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Data Index: 299081 (C4 (Web Text))

Max Activating Token Index: 20

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Text #5

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Data Index: 1421138 (Python Code)

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Text #6

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Text #7

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Text #8

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Data Index: 651126 (C4 (Web Text))

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Text #9

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Data Index: 1517393 (Python Code)

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Text #10

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Text #11

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Text #12

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Data Index: 34689 (C4 (Web Text))

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Text #13

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Data Index: 811482 (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: 541246 (C4 (Web Text))

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Text #17

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Data Index: 648673 (C4 (Web Text))

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Text #18

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Data Index: 134425 (C4 (Web Text))

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Text #19

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Data Index: 1332964 (C4 (Web Text))

Max Activating Token Index: 855

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