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

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

Neuron 34 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: 3.9324. Min Act: -0.1700

Data Index: 241481 (C4 (Web Text))

Max Activating Token Index: 869

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Text #1

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Data Index: 498441 (C4 (Web Text))

Max Activating Token Index: 519

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Text #2

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Max Act: 3.7448. Min Act: -0.1700

Data Index: 895673 (C4 (Web Text))

Max Activating Token Index: 658

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Text #3

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Max Act: 3.7448. Min Act: -0.1700

Data Index: 1154274 (C4 (Web Text))

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Text #4

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Data Index: 1358334 (C4 (Web Text))

Max Activating Token Index: 817

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Text #5

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Text #6

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Data Index: 814053 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 401126 (C4 (Web Text))

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Text #9

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Data Index: 532578 (C4 (Web Text))

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Text #10

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Data Index: 807556 (C4 (Web Text))

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Text #11

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Text #12

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Text #13

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Data Index: 10427 (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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Text #17

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Text #18

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Data Index: 164104 (C4 (Web Text))

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Text #19

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Data Index: 689642 (C4 (Web Text))

Max Activating Token Index: 883

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