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

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

Neuron 36 in Layer 3

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: 4.9994. Min Act: -0.1700

Data Index: 374878 (C4 (Web Text))

Max Activating Token Index: 932

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Text #1

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Data Index: 1315622 (C4 (Web Text))

Max Activating Token Index: 924

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Text #2

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Max Act: 4.6244. Min Act: -0.1700

Data Index: 303041 (C4 (Web Text))

Max Activating Token Index: 996

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Text #3

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Data Index: 735586 (C4 (Web Text))

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Text #4

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Data Index: 1004447 (C4 (Web Text))

Max Activating Token Index: 938

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Text #5

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Text #6

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Data Index: 616961 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 75771 (C4 (Web Text))

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Text #9

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Data Index: 551636 (C4 (Web Text))

Max Activating Token Index: 338

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Text #10

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Text #11

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Text #12

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Data Index: 1215103 (C4 (Web Text))

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Text #13

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Data Index: 708957 (C4 (Web Text))

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Text #14

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Text #15

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Text #16

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Data Index: 1028925 (C4 (Web Text))

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Text #17

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Text #18

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Data Index: 647177 (C4 (Web Text))

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Text #19

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Data Index: 658442 (C4 (Web Text))

Max Activating Token Index: 276

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