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

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

Neuron 1949 in Layer 3

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: 6.2724. Min Act: -0.1700

Data Index: 753235 (C4 (Web Text))

Max Activating Token Index: 793

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Text #1

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Data Index: 519339 (C4 (Web Text))

Max Activating Token Index: 409

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Text #2

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Max Act: 6.2724. Min Act: -0.1700

Data Index: 965485 (C4 (Web Text))

Max Activating Token Index: 764

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Text #3

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Data Index: 866299 (C4 (Web Text))

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Text #4

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Data Index: 311223 (C4 (Web Text))

Max Activating Token Index: 832

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Text #5

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Data Index: 740575 (C4 (Web Text))

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Text #6

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Data Index: 929801 (C4 (Web Text))

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Text #7

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Text #8

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Max Act: 6.2724. Min Act: -0.1700

Data Index: 886009 (C4 (Web Text))

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Text #9

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Data Index: 315198 (C4 (Web Text))

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Text #10

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Data Index: 324685 (C4 (Web Text))

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Text #11

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Text #12

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Text #13

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Data Index: 946994 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1151634 (C4 (Web Text))

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Text #16

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Text #17

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Text #18

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Data Index: 886636 (C4 (Web Text))

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Text #19

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Data Index: 1158748 (C4 (Web Text))

Max Activating Token Index: 504

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