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

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

Neuron 44 in Layer 1

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: 5.6141. Min Act: -0.1700

Data Index: 1333680 (C4 (Web Text))

Max Activating Token Index: 544

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Text #1

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Max Act: 5.5516. Min Act: -0.1700

Data Index: 161422 (C4 (Web Text))

Max Activating Token Index: 824

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Text #2

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Max Act: 5.4891. Min Act: -0.1700

Data Index: 898855 (C4 (Web Text))

Max Activating Token Index: 936

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Text #3

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Max Act: 5.4891. Min Act: -0.1700

Data Index: 1302865 (C4 (Web Text))

Max Activating Token Index: 561

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Text #4

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Max Act: 5.5204. Min Act: -0.1700

Data Index: 191453 (C4 (Web Text))

Max Activating Token Index: 680

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Text #5

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Text #6

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Data Index: 1240703 (C4 (Web Text))

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Text #7

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Data Index: 280261 (C4 (Web Text))

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Text #8

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Data Index: 995315 (C4 (Web Text))

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Text #9

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Data Index: 849629 (C4 (Web Text))

Max Activating Token Index: 496

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Text #10

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Data Index: 321846 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 1196898 (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: 1001395 (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: 472126 (C4 (Web Text))

Max Activating Token Index: 134

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Text #19

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Data Index: 712674 (C4 (Web Text))

Max Activating Token Index: 359

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