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

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

Neuron 1725 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: 3.7344. Min Act: -0.1700

Data Index: 864265 (C4 (Web Text))

Max Activating Token Index: 798

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Text #1

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Data Index: 354330 (C4 (Web Text))

Max Activating Token Index: 417

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Text #2

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Max Act: 3.7188. Min Act: -0.1700

Data Index: 1602020 (Python Code)

Max Activating Token Index: 645

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Text #3

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Max Act: 3.6405. Min Act: -0.1700

Data Index: 386083 (C4 (Web Text))

Max Activating Token Index: 22

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Text #4

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Data Index: 273946 (C4 (Web Text))

Max Activating Token Index: 363

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Text #5

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Data Index: 1285911 (C4 (Web Text))

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Text #6

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Data Index: 335513 (C4 (Web Text))

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Text #7

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Data Index: 93754 (C4 (Web Text))

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Text #8

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Data Index: 1439351 (Python Code)

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Text #9

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Data Index: 29688 (C4 (Web Text))

Max Activating Token Index: 923

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Text #10

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Data Index: 168002 (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: 865945 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1194350 (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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Max Act: 3.4996. Min Act: -0.1700

Data Index: 1043012 (C4 (Web Text))

Max Activating Token Index: 499

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Text #19

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Data Index: 661743 (C4 (Web Text))

Max Activating Token Index: 467

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