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

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

Neuron 1993 in Layer 3

Load this data into an Interactive Neuroscope

See Documentation here

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



Text #0

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Max Act: 7.2823. Min Act: -0.1694

Data Index: 510163 (C4 (Web Text))

Max Activating Token Index: 638

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Text #1

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Max Act: 7.2198. Min Act: -0.1700

Data Index: 941026 (C4 (Web Text))

Max Activating Token Index: 422

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Text #2

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Max Act: 7.1886. Min Act: -0.1699

Data Index: 742866 (C4 (Web Text))

Max Activating Token Index: 621

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Text #3

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Data Index: 931431 (C4 (Web Text))

Max Activating Token Index: 95

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Text #4

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Max Act: 7.0011. Min Act: -0.1700

Data Index: 496437 (C4 (Web Text))

Max Activating Token Index: 925

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Text #5

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Data Index: 1087594 (C4 (Web Text))

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Text #6

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Data Index: 179127 (C4 (Web Text))

Max Activating Token Index: 641

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Text #7

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Text #8

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Data Index: 717800 (C4 (Web Text))

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Text #9

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Data Index: 1036301 (C4 (Web Text))

Max Activating Token Index: 456

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Text #10

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Data Index: 559662 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 68662 (C4 (Web Text))

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Text #13

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Data Index: 858763 (C4 (Web Text))

Max Activating Token Index: 356

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Text #14

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Text #15

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Data Index: 586500 (C4 (Web Text))

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Text #16

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Data Index: 617623 (C4 (Web Text))

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Text #17

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Data Index: 1272058 (C4 (Web Text))

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Text #18

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Data Index: 211780 (C4 (Web Text))

Max Activating Token Index: 785

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Text #19

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Data Index: 159413 (C4 (Web Text))

Max Activating Token Index: 447

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