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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 2

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: 4.5724. Min Act: -0.1700

Data Index: 1345150 (C4 (Web Text))

Max Activating Token Index: 505

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Text #1

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Max Act: 4.4787. Min Act: -0.1700

Data Index: 516896 (C4 (Web Text))

Max Activating Token Index: 750

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Text #2

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Max Act: 4.4474. Min Act: -0.1700

Data Index: 214817 (C4 (Web Text))

Max Activating Token Index: 80

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Text #3

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Data Index: 832840 (C4 (Web Text))

Max Activating Token Index: 898

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Text #4

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Data Index: 1177134 (C4 (Web Text))

Max Activating Token Index: 665

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Text #5

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Data Index: 1070388 (C4 (Web Text))

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Text #6

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Data Index: 986265 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1247513 (C4 (Web Text))

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Text #9

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Data Index: 28894 (C4 (Web Text))

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Text #10

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Data Index: 953515 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 150646 (C4 (Web Text))

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Text #13

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Data Index: 807197 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1195444 (C4 (Web Text))

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Text #16

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Data Index: 612768 (C4 (Web Text))

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Text #17

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Data Index: 567598 (C4 (Web Text))

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Text #18

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Data Index: 1266735 (C4 (Web Text))

Max Activating Token Index: 780

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Text #19

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Max Act: 4.2286. Min Act: -0.1699

Data Index: 801204 (C4 (Web Text))

Max Activating Token Index: 864

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