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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 1877 in Layer 0

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 2.9649. Min Act: -0.1700

Data Index: 1590566 (Python Code)

Max Activating Token Index: 911

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Text #1

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Max Act: 2.9332. Min Act: -0.1700

Data Index: 389377 (C4 (Web Text))

Max Activating Token Index: 181

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Text #2

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Max Act: 2.9332. Min Act: -0.1700

Data Index: 2158 (C4 (Web Text))

Max Activating Token Index: 484

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Text #3

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Max Act: 2.9173. Min Act: -0.1700

Data Index: 829885 (C4 (Web Text))

Max Activating Token Index: 790

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Text #4

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Data Index: 1211852 (C4 (Web Text))

Max Activating Token Index: 74

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Text #5

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Data Index: 1382379 (Python Code)

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Text #6

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Data Index: 1170172 (C4 (Web Text))

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Text #7

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Data Index: 351513 (C4 (Web Text))

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Text #8

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Data Index: 46758 (C4 (Web Text))

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Text #9

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Data Index: 1004213 (C4 (Web Text))

Max Activating Token Index: 542

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Text #10

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Data Index: 175251 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 484141 (C4 (Web Text))

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Text #13

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Data Index: 70618 (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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Max Act: 2.8539. Min Act: -0.1700

Data Index: 1215038 (C4 (Web Text))

Max Activating Token Index: 186

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Text #19

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Data Index: 1209746 (C4 (Web Text))

Max Activating Token Index: 101

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