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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 6 in Layer 2

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 5.5352. Min Act: -0.1700

Data Index: 493330 (C4 (Web Text))

Max Activating Token Index: 359

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Text #1

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Data Index: 1248395 (C4 (Web Text))

Max Activating Token Index: 228

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Text #2

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Data Index: 663864 (C4 (Web Text))

Max Activating Token Index: 719

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Text #3

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Data Index: 18700 (C4 (Web Text))

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Text #4

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Data Index: 72483 (C4 (Web Text))

Max Activating Token Index: 466

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Text #5

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Text #6

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Data Index: 845917 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1184869 (C4 (Web Text))

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Text #9

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Data Index: 1214729 (C4 (Web Text))

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Text #10

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Text #11

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Text #12

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Data Index: 753623 (C4 (Web Text))

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Text #13

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Text #14

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Text #15

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Text #16

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Text #17

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Text #18

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Data Index: 49630 (C4 (Web Text))

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Text #19

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Data Index: 624367 (C4 (Web Text))

Max Activating Token Index: 697

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