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

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

Neuron 32 in Layer 2

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: 3.6299. Min Act: -0.1700

Data Index: 1258664 (C4 (Web Text))

Max Activating Token Index: 650

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Text #1

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Max Act: 3.5986. Min Act: -0.1700

Data Index: 162160 (C4 (Web Text))

Max Activating Token Index: 890

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Text #2

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Data Index: 700062 (C4 (Web Text))

Max Activating Token Index: 786

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Text #3

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Data Index: 206775 (C4 (Web Text))

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Text #4

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Data Index: 773181 (C4 (Web Text))

Max Activating Token Index: 484

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Text #5

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Text #6

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Data Index: 504909 (C4 (Web Text))

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Text #7

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Data Index: 113011 (C4 (Web Text))

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Text #8

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Data Index: 993407 (C4 (Web Text))

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Text #9

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Data Index: 978236 (C4 (Web Text))

Max Activating Token Index: 718

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Text #10

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Text #11

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Text #12

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Data Index: 851432 (C4 (Web Text))

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Text #13

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Data Index: 746755 (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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Data Index: 962225 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 800915 (C4 (Web Text))

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Text #19

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Data Index: 1045313 (C4 (Web Text))

Max Activating Token Index: 745

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