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

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

Neuron 1880 in Layer 0

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



Text #0

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Max Act: 2.4844. Min Act: -0.1700

Data Index: 1553857 (Python Code)

Max Activating Token Index: 304

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Text #1

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Max Act: 2.4681. Min Act: -0.1700

Data Index: 1492416 (Python Code)

Max Activating Token Index: 202

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Text #2

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Max Act: 2.4519. Min Act: -0.1700

Data Index: 1526778 (Python Code)

Max Activating Token Index: 1023

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Text #3

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Max Act: 2.4031. Min Act: -0.1700

Data Index: 1443773 (Python Code)

Max Activating Token Index: 11

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Text #4

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Max Act: 2.3867. Min Act: -0.1700

Data Index: 764569 (C4 (Web Text))

Max Activating Token Index: 308

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Text #5

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Data Index: 1503771 (Python Code)

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Text #6

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Data Index: 163451 (C4 (Web Text))

Max Activating Token Index: 328

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Text #7

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Data Index: 1620528 (Python Code)

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Text #8

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Data Index: 1504829 (Python Code)

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Text #9

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Data Index: 1493985 (Python Code)

Max Activating Token Index: 105

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Text #10

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Data Index: 1511299 (Python Code)

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Text #11

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Data Index: 1441901 (Python Code)

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Data Index: 1520891 (Python Code)

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Data Index: 1364912 (Python Code)

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Text #14

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Data Index: 1596616 (Python Code)

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Text #15

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Data Index: 1596919 (Python Code)

Max Activating Token Index: 244

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Text #16

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Data Index: 1618004 (Python Code)

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Text #17

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Data Index: 1631344 (Python Code)

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Text #18

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Data Index: 1420819 (Python Code)

Max Activating Token Index: 52

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Text #19

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Max Act: 2.3541. Min Act: -0.1700

Data Index: 1480285 (Python Code)

Max Activating Token Index: 739

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