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

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

Neuron 1296 in Layer 2

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: 4.6668. Min Act: -0.1700

Data Index: 723663 (C4 (Web Text))

Max Activating Token Index: 159

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Text #1

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Max Act: 4.5730. Min Act: -0.1700

Data Index: 345097 (C4 (Web Text))

Max Activating Token Index: 166

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Text #2

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Max Act: 4.5418. Min Act: -0.1700

Data Index: 812831 (C4 (Web Text))

Max Activating Token Index: 263

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Text #3

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Max Act: 4.5887. Min Act: -0.1700

Data Index: 1134392 (C4 (Web Text))

Max Activating Token Index: 293

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Text #4

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Data Index: 1244066 (C4 (Web Text))

Max Activating Token Index: 411

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Text #5

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Data Index: 368826 (C4 (Web Text))

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Text #6

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Data Index: 1146794 (C4 (Web Text))

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Text #7

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Data Index: 1341694 (C4 (Web Text))

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Text #8

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Max Act: 4.5418. Min Act: -0.1700

Data Index: 801545 (C4 (Web Text))

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Text #9

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Data Index: 349349 (C4 (Web Text))

Max Activating Token Index: 712

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Text #10

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Data Index: 1369972 (Python Code)

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Text #11

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Text #12

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Data Index: 1025342 (C4 (Web Text))

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Text #13

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Data Index: 1559350 (Python Code)

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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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Data Index: 483335 (C4 (Web Text))

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Text #18

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Data Index: 812289 (C4 (Web Text))

Max Activating Token Index: 857

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Text #19

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Data Index: 290833 (C4 (Web Text))

Max Activating Token Index: 742

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