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

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

Neuron 790 in Layer 2

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('solu-3l')

Text #0

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Max Act: 0.0779. Min Act: -0.0003

Data Index: 662487 (C4 (Web Text))

Max Activating Token Index: 350

Text #1

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Max Act: 0.0759. Min Act: -0.0002

Data Index: 205785 (C4 (Web Text))

Max Activating Token Index: 327

Text #2

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Max Act: 0.0737. Min Act: -0.0003

Data Index: 618015 (C4 (Web Text))

Max Activating Token Index: 798

Text #3

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Max Act: 0.0741. Min Act: -0.0003

Data Index: 131731 (C4 (Web Text))

Max Activating Token Index: 498

Text #4

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Max Act: 0.0717. Min Act: -0.0004

Data Index: 1205193 (C4 (Web Text))

Max Activating Token Index: 554

Text #5

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Max Act: 0.0691. Min Act: -0.0004

Data Index: 231706 (C4 (Web Text))

Max Activating Token Index: 774

Text #6

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Max Act: 0.0677. Min Act: -0.0002

Data Index: 1068092 (C4 (Web Text))

Max Activating Token Index: 369

Text #7

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Data Index: 95944 (C4 (Web Text))

Max Activating Token Index: 102

Text #8

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Data Index: 612167 (C4 (Web Text))

Max Activating Token Index: 749

Text #9

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Max Act: 0.0610. Min Act: -0.0003

Data Index: 1251928 (C4 (Web Text))

Max Activating Token Index: 523

Text #10

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Data Index: 288617 (C4 (Web Text))

Max Activating Token Index: 758

Text #11

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Data Index: 1126037 (C4 (Web Text))

Max Activating Token Index: 259

Text #12

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Data Index: 106918 (C4 (Web Text))

Max Activating Token Index: 60

Text #13

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Max Act: 0.0585. Min Act: -0.0003

Data Index: 468441 (C4 (Web Text))

Max Activating Token Index: 733

Text #14

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Data Index: 579167 (C4 (Web Text))

Max Activating Token Index: 626

Text #15

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Max Activating Token Index: 740

Text #16

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Max Activating Token Index: 978

Text #17

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Data Index: 386424 (C4 (Web Text))

Max Activating Token Index: 79

Text #18

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Data Index: 507935 (C4 (Web Text))

Max Activating Token Index: 116

Text #19

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Data Index: 266091 (C4 (Web Text))

Max Activating Token Index: 1022