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

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

Neuron 1680 in Layer 2

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: 3.3403. Min Act: -0.1700

Data Index: 1652484 (Python Code)

Max Activating Token Index: 1004

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Text #1

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Max Act: 3.3246. Min Act: -0.1700

Data Index: 1189788 (C4 (Web Text))

Max Activating Token Index: 415

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Text #2

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Data Index: 542352 (C4 (Web Text))

Max Activating Token Index: 628

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Text #3

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Data Index: 717361 (C4 (Web Text))

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Text #4

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Data Index: 587657 (C4 (Web Text))

Max Activating Token Index: 189

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Text #5

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Text #6

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Text #7

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Text #8

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Data Index: 199813 (C4 (Web Text))

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Text #9

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Data Index: 761232 (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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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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Max Activating Token Index: 398

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Text #19

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Data Index: 1069989 (C4 (Web Text))

Max Activating Token Index: 692

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