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

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

Neuron 1097 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: 0.0621. Min Act: -0.0003

Data Index: 92077 (C4 (Web Text))

Max Activating Token Index: 347

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Text #1

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Max Act: 0.0551. Min Act: -0.0004

Data Index: 656755 (C4 (Web Text))

Max Activating Token Index: 932

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Truncated

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Text #2

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Max Act: 0.0539. Min Act: -0.0003

Data Index: 649410 (C4 (Web Text))

Max Activating Token Index: 37

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Text #3

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Max Act: 0.0544. Min Act: -0.0003

Data Index: 960318 (C4 (Web Text))

Max Activating Token Index: 644

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Truncated

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Text #4

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Data Index: 1595779 (Python Code)

Max Activating Token Index: 390

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Truncated

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Text #5

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Max Act: 0.0514. Min Act: -0.0003

Data Index: 26070 (C4 (Web Text))

Max Activating Token Index: 938

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Text #6

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Data Index: 164264 (C4 (Web Text))

Max Activating Token Index: 41

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Text #7

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Data Index: 640391 (C4 (Web Text))

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Truncated

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Text #8

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Data Index: 837646 (C4 (Web Text))

Max Activating Token Index: 357

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Text #9

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Data Index: 234546 (C4 (Web Text))

Max Activating Token Index: 953

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Text #10

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Data Index: 619227 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 650954 (C4 (Web Text))

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Text #13

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Text #14

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Data Index: 1068517 (C4 (Web Text))

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Text #15

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Data Index: 1641023 (Python Code)

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Text #16

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Text #17

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Data Index: 1023577 (C4 (Web Text))

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Text #18

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Data Index: 1238562 (C4 (Web Text))

Max Activating Token Index: 750

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Text #19

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Data Index: 1172131 (C4 (Web Text))

Max Activating Token Index: 466

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