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

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

Neuron 1984 in Layer 1

Load this data into an Interactive Neuroscope

See Documentation here

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



Text #0

Max Range: 4.1573. Min Range: -4.1573

Max Act: 4.1573. Min Act: -0.1700

Data Index: 735654 (C4 (Web Text))

Max Activating Token Index: 184

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Text #1

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Max Act: 4.0948. Min Act: -0.1700

Data Index: 773101 (C4 (Web Text))

Max Activating Token Index: 779

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Text #2

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Max Act: 4.0322. Min Act: -0.1700

Data Index: 1643061 (Python Code)

Max Activating Token Index: 647

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Text #3

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Max Act: 4.0010. Min Act: -0.1700

Data Index: 398789 (C4 (Web Text))

Max Activating Token Index: 735

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Text #4

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Max Act: 3.9697. Min Act: -0.1700

Data Index: 120936 (C4 (Web Text))

Max Activating Token Index: 259

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Text #5

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Max Act: 4.0010. Min Act: -0.1700

Data Index: 1271019 (C4 (Web Text))

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Text #6

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Data Index: 486244 (C4 (Web Text))

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Text #7

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Data Index: 1421080 (Python Code)

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Text #8

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Data Index: 1193467 (C4 (Web Text))

Max Activating Token Index: 719

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Text #9

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Data Index: 1338486 (C4 (Web Text))

Max Activating Token Index: 364

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Text #10

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Data Index: 663957 (C4 (Web Text))

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Text #11

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Data Index: 651867 (C4 (Web Text))

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Text #12

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Data Index: 222057 (C4 (Web Text))

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Text #13

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Data Index: 1165584 (C4 (Web Text))

Max Activating Token Index: 484

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Text #14

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Text #15

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Data Index: 672807 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 1144105 (C4 (Web Text))

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Text #18

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Data Index: 1526271 (Python Code)

Max Activating Token Index: 906

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Text #19

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Data Index: 541351 (C4 (Web Text))

Max Activating Token Index: 370

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