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

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

Neuron 1217 in Layer 0

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



Text #0

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Max Act: 3.0277. Min Act: -0.1700

Data Index: 1412218 (Python Code)

Max Activating Token Index: 290

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Text #1

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Max Act: 3.0119. Min Act: -0.1700

Data Index: 1452408 (Python Code)

Max Activating Token Index: 989

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Text #2

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Max Act: 2.9961. Min Act: -0.1700

Data Index: 1562384 (Python Code)

Max Activating Token Index: 811

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Text #3

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Max Act: 2.9644. Min Act: -0.1700

Data Index: 1513833 (Python Code)

Max Activating Token Index: 191

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Text #4

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Max Act: 2.9644. Min Act: -0.1700

Data Index: 185276 (C4 (Web Text))

Max Activating Token Index: 1023

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Text #5

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Data Index: 1436399 (Python Code)

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Data Index: 1079325 (C4 (Web Text))

Max Activating Token Index: 476

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Text #7

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Data Index: 1593593 (Python Code)

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Text #8

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Data Index: 1361184 (Python Code)

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Text #9

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Data Index: 1655330 (Python Code)

Max Activating Token Index: 380

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Data Index: 1403108 (Python Code)

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Text #11

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Data Index: 1585800 (Python Code)

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Text #12

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Data Index: 1642994 (Python Code)

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Data Index: 1377207 (Python Code)

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Text #14

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Data Index: 1477699 (Python Code)

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Text #15

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Data Index: 1531039 (Python Code)

Max Activating Token Index: 236

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Text #16

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Data Index: 1632454 (Python Code)

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Text #17

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Data Index: 1519548 (Python Code)

Max Activating Token Index: 962

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Text #18

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Data Index: 1605611 (Python Code)

Max Activating Token Index: 28

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Text #19

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Max Act: 2.8693. Min Act: -0.1700

Data Index: 1499011 (Python Code)

Max Activating Token Index: 654

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