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

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

Neuron 1077 in Layer 2

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: 3.4923. Min Act: -0.1700

Data Index: 710426 (C4 (Web Text))

Max Activating Token Index: 722

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Text #1

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Max Act: 3.4453. Min Act: -0.1700

Data Index: 737377 (C4 (Web Text))

Max Activating Token Index: 476

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Text #2

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Max Act: 3.4610. Min Act: -0.1700

Data Index: 44115 (C4 (Web Text))

Max Activating Token Index: 446

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Text #3

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Data Index: 1084446 (C4 (Web Text))

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Text #4

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Data Index: 1012187 (C4 (Web Text))

Max Activating Token Index: 626

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Text #5

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Text #6

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Data Index: 922495 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1078877 (C4 (Web Text))

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Text #9

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Data Index: 1129101 (C4 (Web Text))

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Text #10

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Text #11

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Text #12

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Text #13

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Data Index: 1286017 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1262366 (C4 (Web Text))

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Text #16

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Text #17

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Text #18

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Data Index: 942379 (C4 (Web Text))

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Text #19

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Data Index: 79952 (C4 (Web Text))

Max Activating Token Index: 933

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