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

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

Neuron 57 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: 2.9305. Min Act: -0.1700

Data Index: 527866 (C4 (Web Text))

Max Activating Token Index: 987

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Text #1

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Data Index: 1184444 (C4 (Web Text))

Max Activating Token Index: 167

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Text #2

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Data Index: 236021 (C4 (Web Text))

Max Activating Token Index: 403

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Text #3

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Max Act: 2.8988. Min Act: -0.1700

Data Index: 99565 (C4 (Web Text))

Max Activating Token Index: 414

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Text #4

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Max Act: 2.8670. Min Act: -0.1700

Data Index: 231484 (C4 (Web Text))

Max Activating Token Index: 424

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Text #5

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Data Index: 1301167 (C4 (Web Text))

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Text #6

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Data Index: 1150941 (C4 (Web Text))

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Text #7

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Data Index: 440973 (C4 (Web Text))

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Text #8

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Data Index: 259290 (C4 (Web Text))

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Text #9

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Data Index: 1000110 (C4 (Web Text))

Max Activating Token Index: 1007

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Text #10

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Text #11

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Data Index: 300913 (C4 (Web Text))

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Text #12

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Data Index: 1325317 (C4 (Web Text))

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Text #13

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Data Index: 27517 (C4 (Web Text))

Max Activating Token Index: 845

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Text #14

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Text #15

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Text #16

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Data Index: 1357013 (C4 (Web Text))

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Text #17

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Data Index: 1088795 (C4 (Web Text))

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Text #18

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Data Index: 654970 (C4 (Web Text))

Max Activating Token Index: 120

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Text #19

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Data Index: 1080644 (C4 (Web Text))

Max Activating Token Index: 742

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