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

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

Neuron 1819 in Layer 1

Load this data into an Interactive Neuroscope

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



Text #0

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Max Act: 4.2181. Min Act: -0.1700

Data Index: 1510675 (Python Code)

Max Activating Token Index: 854

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Text #1

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Max Act: 3.9367. Min Act: -0.1700

Data Index: 391442 (C4 (Web Text))

Max Activating Token Index: 186

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Text #2

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Max Act: 3.9367. Min Act: -0.1700

Data Index: 367376 (C4 (Web Text))

Max Activating Token Index: 1002

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Text #3

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Max Act: 3.9367. Min Act: -0.1700

Data Index: 529583 (C4 (Web Text))

Max Activating Token Index: 993

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Text #4

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Data Index: 241893 (C4 (Web Text))

Max Activating Token Index: 786

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Text #5

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Data Index: 178616 (C4 (Web Text))

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Text #6

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Data Index: 529909 (C4 (Web Text))

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Text #7

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Data Index: 1505151 (Python Code)

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Text #8

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Data Index: 1420597 (Python Code)

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Text #9

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Data Index: 196392 (C4 (Web Text))

Max Activating Token Index: 146

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Text #10

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Data Index: 1149689 (C4 (Web Text))

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Text #11

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Data Index: 161622 (C4 (Web Text))

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Text #12

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Data Index: 1219476 (C4 (Web Text))

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Text #13

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Text #14

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Text #15

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Data Index: 609889 (C4 (Web Text))

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Text #16

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Data Index: 636371 (C4 (Web Text))

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Text #17

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Max Act: 3.8429. Min Act: -0.1700

Data Index: 1058971 (C4 (Web Text))

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Text #18

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Data Index: 906700 (C4 (Web Text))

Max Activating Token Index: 794

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Text #19

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Data Index: 1181881 (C4 (Web Text))

Max Activating Token Index: 238

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