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

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

Neuron 737 in Layer 0

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

Text #0

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Max Act: 7.0441. Min Act: -0.1700

Data Index: 1565091 (Python Code)

Max Activating Token Index: 56

Text #1

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Max Act: 6.7941. Min Act: -0.1700

Data Index: 1365555 (Python Code)

Max Activating Token Index: 37

Text #2

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Data Index: 1531965 (Python Code)

Max Activating Token Index: 15

Text #3

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Max Act: 6.7004. Min Act: -0.1700

Data Index: 1422144 (Python Code)

Max Activating Token Index: 69

Text #4

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Max Act: 6.6691. Min Act: -0.1700

Data Index: 1410520 (Python Code)

Max Activating Token Index: 865

Text #5

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Data Index: 1641248 (Python Code)

Max Activating Token Index: 292

Text #6

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Data Index: 1627732 (Python Code)

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Text #7

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Data Index: 1480113 (Python Code)

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Text #8

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Data Index: 1492966 (Python Code)

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Text #9

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Data Index: 1532346 (Python Code)

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Text #10

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Data Index: 1409543 (Python Code)

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Text #11

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Data Index: 1493474 (Python Code)

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Text #12

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Data Index: 1361599 (Python Code)

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Text #13

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Data Index: 1583444 (Python Code)

Max Activating Token Index: 831

Text #14

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Data Index: 1375261 (Python Code)

Max Activating Token Index: 371

Text #15

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Data Index: 1640198 (Python Code)

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Text #16

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Data Index: 1540416 (Python Code)

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Text #17

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Data Index: 1449797 (Python Code)

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Text #18

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Data Index: 1586063 (Python Code)

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Text #19

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Max Act: 6.4191. Min Act: -0.1700

Data Index: 1365229 (Python Code)

Max Activating Token Index: 462