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

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

Neuron 2038 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: 3.0675. Min Act: -0.1700

Data Index: 1046903 (C4 (Web Text))

Max Activating Token Index: 926

Text #1

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Max Activating Token Index: 937

Text #2

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Max Act: 3.0043. Min Act: -0.1700

Data Index: 588430 (C4 (Web Text))

Max Activating Token Index: 966

Text #3

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Data Index: 474685 (C4 (Web Text))

Max Activating Token Index: 575

Text #4

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Max Activating Token Index: 790

Text #5

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Data Index: 245209 (C4 (Web Text))

Max Activating Token Index: 534

Text #6

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Max Activating Token Index: 897

Text #7

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Max Activating Token Index: 90

Text #8

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Max Activating Token Index: 981

Text #9

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Max Activating Token Index: 888

Text #10

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Max Activating Token Index: 1014

Text #11

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Max Activating Token Index: 670

Text #12

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Data Index: 995043 (C4 (Web Text))

Max Activating Token Index: 691

Text #13

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Data Index: 1103166 (C4 (Web Text))

Max Activating Token Index: 820

Text #14

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Max Activating Token Index: 851

Text #15

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Text #16

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Max Activating Token Index: 729

Text #17

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Max Activating Token Index: 808

Text #18

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Max Activating Token Index: 683

Text #19

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Data Index: 583602 (C4 (Web Text))

Max Activating Token Index: 896