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

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

Neuron 59 in Layer 3

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: 4.9214. Min Act: -0.1700

Data Index: 437248 (C4 (Web Text))

Max Activating Token Index: 530

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Text #1

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Max Act: 4.8589. Min Act: -0.1700

Data Index: 948240 (C4 (Web Text))

Max Activating Token Index: 977

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Text #2

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Max Act: 4.9214. Min Act: -0.1700

Data Index: 1590449 (Python Code)

Max Activating Token Index: 210

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Text #3

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Max Act: 4.8901. Min Act: -0.1700

Data Index: 63464 (C4 (Web Text))

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Text #4

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Data Index: 985064 (C4 (Web Text))

Max Activating Token Index: 531

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Text #5

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Data Index: 202423 (C4 (Web Text))

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Text #6

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Data Index: 652106 (C4 (Web Text))

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Text #7

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Data Index: 1153054 (C4 (Web Text))

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Text #8

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Data Index: 313285 (C4 (Web Text))

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Text #9

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Data Index: 1347125 (C4 (Web Text))

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Text #10

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Data Index: 766680 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 216323 (C4 (Web Text))

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Text #13

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Data Index: 643704 (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: 481200 (C4 (Web Text))

Max Activating Token Index: 87

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Text #19

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Data Index: 218259 (C4 (Web Text))

Max Activating Token Index: 393

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