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

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

Neuron 17 in Layer 1

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: 5.2969. Min Act: -0.1700

Data Index: 531056 (C4 (Web Text))

Max Activating Token Index: 1004

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Text #1

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Max Act: 5.1407. Min Act: -0.1700

Data Index: 704892 (C4 (Web Text))

Max Activating Token Index: 54

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Text #2

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Max Act: 5.2344. Min Act: -0.1700

Data Index: 434100 (C4 (Web Text))

Max Activating Token Index: 842

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Text #3

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Max Act: 5.1719. Min Act: -0.1700

Data Index: 890134 (C4 (Web Text))

Max Activating Token Index: 812

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Text #4

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Max Act: 5.1094. Min Act: -0.1700

Data Index: 735316 (C4 (Web Text))

Max Activating Token Index: 524

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Text #5

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Data Index: 1062220 (C4 (Web Text))

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Text #6

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Data Index: 1106441 (C4 (Web Text))

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Text #7

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Data Index: 631913 (C4 (Web Text))

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Text #8

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Data Index: 136084 (C4 (Web Text))

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Text #9

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Data Index: 206671 (C4 (Web Text))

Max Activating Token Index: 949

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Text #10

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Data Index: 629456 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 215163 (C4 (Web Text))

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Text #13

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Data Index: 280296 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 786465 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 344373 (C4 (Web Text))

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Text #18

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Data Index: 1122478 (C4 (Web Text))

Max Activating Token Index: 897

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Text #19

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Data Index: 320165 (C4 (Web Text))

Max Activating Token Index: 886

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