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

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

Neuron 276 in Layer 1

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: 3.7098. Min Act: -0.1700

Data Index: 1468203 (Python Code)

Max Activating Token Index: 20

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Text #1

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Max Act: 3.6629. Min Act: -0.1700

Data Index: 1004092 (C4 (Web Text))

Max Activating Token Index: 221

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Text #2

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Max Act: 3.6159. Min Act: -0.1700

Data Index: 143280 (C4 (Web Text))

Max Activating Token Index: 443

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Text #3

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Max Act: 3.6159. Min Act: -0.1700

Data Index: 1126598 (C4 (Web Text))

Max Activating Token Index: 281

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Text #4

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Max Act: 3.6316. Min Act: -0.1700

Data Index: 66248 (C4 (Web Text))

Max Activating Token Index: 582

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Text #5

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Max Act: 3.6159. Min Act: -0.1700

Data Index: 107839 (C4 (Web Text))

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Text #6

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Data Index: 1230181 (C4 (Web Text))

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Text #7

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Data Index: 807931 (C4 (Web Text))

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Text #8

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Data Index: 706238 (C4 (Web Text))

Max Activating Token Index: 498

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Text #9

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Data Index: 1166404 (C4 (Web Text))

Max Activating Token Index: 829

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Text #10

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Data Index: 1066910 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 798015 (C4 (Web Text))

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Text #13

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Data Index: 835647 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 383479 (C4 (Web Text))

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Text #16

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Max Activating Token Index: 612

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Text #17

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Data Index: 1464916 (Python Code)

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Text #18

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Max Act: 3.5220. Min Act: -0.1700

Data Index: 668295 (C4 (Web Text))

Max Activating Token Index: 129

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Text #19

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Data Index: 669921 (C4 (Web Text))

Max Activating Token Index: 369

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