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

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

Neuron 1368 in Layer 3

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: 5.2093. Min Act: -0.1700

Data Index: 885781 (C4 (Web Text))

Max Activating Token Index: 1007

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Text #1

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Max Act: 5.1780. Min Act: -0.1700

Data Index: 1570235 (Python Code)

Max Activating Token Index: 172

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Text #2

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Max Act: 5.1780. Min Act: -0.1700

Data Index: 607606 (C4 (Web Text))

Max Activating Token Index: 490

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Text #3

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Max Act: 5.0999. Min Act: -0.1700

Data Index: 439727 (C4 (Web Text))

Max Activating Token Index: 715

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Text #4

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Max Act: 5.0061. Min Act: -0.1700

Data Index: 605999 (C4 (Web Text))

Max Activating Token Index: 518

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Text #5

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Data Index: 934786 (C4 (Web Text))

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Text #6

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Data Index: 369902 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 940422 (C4 (Web Text))

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Text #9

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Data Index: 976685 (C4 (Web Text))

Max Activating Token Index: 884

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Text #10

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Data Index: 598198 (C4 (Web Text))

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Text #11

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Text #12

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Text #13

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Data Index: 1185049 (C4 (Web Text))

Max Activating Token Index: 903

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Text #14

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Text #15

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Text #16

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Data Index: 91233 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 1125417 (C4 (Web Text))

Max Activating Token Index: 32

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Text #19

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Data Index: 179245 (C4 (Web Text))

Max Activating Token Index: 281

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