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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 36 in Layer 2

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 5.5836. Min Act: -0.1700

Data Index: 557300 (C4 (Web Text))

Max Activating Token Index: 927

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Text #1

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Data Index: 93344 (C4 (Web Text))

Max Activating Token Index: 501

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Text #2

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Data Index: 693749 (C4 (Web Text))

Max Activating Token Index: 918

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Text #3

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Data Index: 396972 (C4 (Web Text))

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Text #4

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Data Index: 245311 (C4 (Web Text))

Max Activating Token Index: 169

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Text #5

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Data Index: 1169223 (C4 (Web Text))

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Text #6

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Data Index: 1278347 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1189571 (C4 (Web Text))

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Text #9

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Data Index: 472939 (C4 (Web Text))

Max Activating Token Index: 887

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Text #10

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Text #11

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Data Index: 416653 (C4 (Web Text))

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Text #12

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Data Index: 1310537 (C4 (Web Text))

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Text #13

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Data Index: 1045654 (C4 (Web Text))

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Text #14

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Text #15

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Text #16

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Text #17

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Text #18

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Data Index: 68361 (C4 (Web Text))

Max Activating Token Index: 454

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Text #19

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Data Index: 216314 (C4 (Web Text))

Max Activating Token Index: 513

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