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

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

Neuron 71 in Layer 1

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: 4.8565. Min Act: -0.1700

Data Index: 1209728 (C4 (Web Text))

Max Activating Token Index: 588

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Text #1

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Data Index: 1118759 (C4 (Web Text))

Max Activating Token Index: 905

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Text #2

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Data Index: 147724 (C4 (Web Text))

Max Activating Token Index: 481

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Text #3

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Data Index: 836379 (C4 (Web Text))

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Text #4

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Data Index: 1324543 (C4 (Web Text))

Max Activating Token Index: 541

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Text #5

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Data Index: 1228831 (C4 (Web Text))

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Text #6

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Data Index: 1039244 (C4 (Web Text))

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Text #7

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Data Index: 225372 (C4 (Web Text))

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Text #8

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Data Index: 572921 (C4 (Web Text))

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Text #9

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Data Index: 1012871 (C4 (Web Text))

Max Activating Token Index: 996

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Text #10

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Data Index: 641826 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 1095959 (C4 (Web Text))

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Text #13

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Data Index: 40052 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 172831 (C4 (Web Text))

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Text #16

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Data Index: 503284 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 502948 (C4 (Web Text))

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Text #19

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Data Index: 890792 (C4 (Web Text))

Max Activating Token Index: 314

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