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

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

Neuron 41 in Layer 1

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

Max Range: 3.9682. Min Range: -3.9682

Max Act: 3.9682. Min Act: -0.1700

Data Index: 43767 (C4 (Web Text))

Max Activating Token Index: 1023

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Text #1

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Max Act: 3.8744. Min Act: -0.1700

Data Index: 754533 (C4 (Web Text))

Max Activating Token Index: 286

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Text #2

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Max Act: 3.8118. Min Act: -0.1700

Data Index: 74927 (C4 (Web Text))

Max Activating Token Index: 792

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Text #3

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Max Act: 3.8431. Min Act: -0.1700

Data Index: 100926 (C4 (Web Text))

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Text #4

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Data Index: 2690 (C4 (Web Text))

Max Activating Token Index: 912

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Text #5

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Text #6

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Data Index: 703034 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 435618 (C4 (Web Text))

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Text #9

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Data Index: 538519 (C4 (Web Text))

Max Activating Token Index: 690

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Text #10

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Data Index: 282341 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 928131 (C4 (Web Text))

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Text #13

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Data Index: 1107898 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1309715 (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: 937743 (C4 (Web Text))

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Text #19

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Data Index: 1227846 (C4 (Web Text))

Max Activating Token Index: 1023

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