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

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

Neuron 999 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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Data Index: 1081969 (C4 (Web Text))

Max Activating Token Index: 23

Text #1

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Max Activating Token Index: 145

Text #2

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Max Activating Token Index: 534

Text #3

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Data Index: 916166 (C4 (Web Text))

Max Activating Token Index: 38

Text #4

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Max Activating Token Index: 953

Text #5

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Max Activating Token Index: 343

Text #6

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Max Activating Token Index: 287

Text #7

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Max Activating Token Index: 632

Text #8

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Max Activating Token Index: 955

Text #9

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Max Activating Token Index: 431

Text #10

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Max Activating Token Index: 49

Text #11

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Max Activating Token Index: 239

Text #12

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Max Activating Token Index: 482

Text #13

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Data Index: 496153 (C4 (Web Text))

Max Activating Token Index: 439

Text #14

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Max Activating Token Index: 657

Text #15

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Max Activating Token Index: 955

Text #16

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Max Activating Token Index: 195

Text #17

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Max Activating Token Index: 877

Text #18

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Max Activating Token Index: 98

Text #19

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Max Act: 3.5016. Min Act: -0.1700

Data Index: 1086674 (C4 (Web Text))

Max Activating Token Index: 943