Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 524 in Layer 0

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')

Text #0

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Max Act: 3.6091. Min Act: -0.1700

Data Index: 1099027 (C4 (Web Text))

Max Activating Token Index: 480

Text #1

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Max Activating Token Index: 213

Text #2

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Max Act: 3.5778. Min Act: -0.1700

Data Index: 225472 (C4 (Web Text))

Max Activating Token Index: 617

Text #3

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Max Act: 3.5778. Min Act: -0.1700

Data Index: 863471 (C4 (Web Text))

Max Activating Token Index: 209

Text #4

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Max Activating Token Index: 832

Text #5

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Max Activating Token Index: 367

Text #6

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Max Activating Token Index: 973

Text #7

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Max Activating Token Index: 833

Text #8

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Data Index: 226290 (C4 (Web Text))

Max Activating Token Index: 393

Text #9

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Max Activating Token Index: 286

Text #10

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Max Activating Token Index: 314

Text #11

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Max Activating Token Index: 454

Text #12

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Max Activating Token Index: 181

Text #13

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Data Index: 1301518 (C4 (Web Text))

Max Activating Token Index: 828

Text #14

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Max Activating Token Index: 914

Text #15

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Max Activating Token Index: 825

Text #16

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Text #17

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Max Activating Token Index: 1003

Text #18

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Max Activating Token Index: 219

Text #19

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Data Index: 470832 (C4 (Web Text))

Max Activating Token Index: 120