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

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

Neuron 52 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: 6.3186. Min Act: -0.1700

Data Index: 228282 (C4 (Web Text))

Max Activating Token Index: 512

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Text #1

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Data Index: 1044061 (C4 (Web Text))

Max Activating Token Index: 437

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Text #2

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Max Act: 6.1623. Min Act: -0.1700

Data Index: 361463 (C4 (Web Text))

Max Activating Token Index: 554

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Text #3

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Max Act: 6.1311. Min Act: -0.1700

Data Index: 1200673 (C4 (Web Text))

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Text #4

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Data Index: 688292 (C4 (Web Text))

Max Activating Token Index: 516

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Text #5

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Data Index: 718087 (C4 (Web Text))

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Text #6

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Text #7

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Text #8

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Data Index: 147932 (C4 (Web Text))

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Text #9

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Data Index: 893949 (C4 (Web Text))

Max Activating Token Index: 621

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Text #10

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Data Index: 348670 (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: 1257267 (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: 561567 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 716321 (C4 (Web Text))

Max Activating Token Index: 851

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Text #19

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Data Index: 470341 (C4 (Web Text))

Max Activating Token Index: 370

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