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

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

Neuron 51 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: 2.9055. Min Act: -0.1700

Data Index: 1022875 (C4 (Web Text))

Max Activating Token Index: 10

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Text #1

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Data Index: 1047544 (C4 (Web Text))

Max Activating Token Index: 640

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Text #2

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Max Act: 2.8737. Min Act: -0.1700

Data Index: 958216 (C4 (Web Text))

Max Activating Token Index: 624

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Text #3

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Max Act: 2.8419. Min Act: -0.1700

Data Index: 542679 (C4 (Web Text))

Max Activating Token Index: 890

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Text #4

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Data Index: 1265628 (C4 (Web Text))

Max Activating Token Index: 74

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Text #5

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Text #6

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Data Index: 275957 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 448742 (C4 (Web Text))

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Text #9

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Data Index: 653621 (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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Data Index: 324379 (C4 (Web Text))

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Text #13

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Data Index: 1121111 (C4 (Web Text))

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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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Data Index: 433925 (C4 (Web Text))

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Text #19

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Data Index: 436451 (C4 (Web Text))

Max Activating Token Index: 281

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