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

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

Neuron 1915 in Layer 0

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

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Max Act: 2.7872. Min Act: -0.1700

Data Index: 1369633 (Python Code)

Max Activating Token Index: 1000

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Text #1

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Max Act: 2.7553. Min Act: -0.1700

Data Index: 1653122 (Python Code)

Max Activating Token Index: 563

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Text #2

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Max Act: 2.7553. Min Act: -0.1700

Data Index: 1657065 (Python Code)

Max Activating Token Index: 1016

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Text #3

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Max Act: 2.7234. Min Act: -0.1700

Data Index: 86587 (C4 (Web Text))

Max Activating Token Index: 478

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Text #4

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Data Index: 1493883 (Python Code)

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Text #5

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Data Index: 1553819 (Python Code)

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Data Index: 1517677 (Python Code)

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Text #7

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Data Index: 752926 (C4 (Web Text))

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Text #8

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Data Index: 1565455 (Python Code)

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Text #9

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Data Index: 1394842 (Python Code)

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Text #10

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Data Index: 1544252 (Python Code)

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Text #11

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Data Index: 1457498 (Python Code)

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Data Index: 1422692 (Python Code)

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Data Index: 1577438 (Python Code)

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Text #14

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Data Index: 1586288 (Python Code)

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Text #15

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Data Index: 1630001 (Python Code)

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Text #16

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Text #17

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Data Index: 1450517 (Python Code)

Max Activating Token Index: 563

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Text #18

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Data Index: 1366827 (Python Code)

Max Activating Token Index: 77

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Text #19

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Data Index: 1373298 (Python Code)

Max Activating Token Index: 673

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