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

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

Neuron 220 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: 4.9078. Min Act: -0.1700

Data Index: 207293 (C4 (Web Text))

Max Activating Token Index: 434

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Text #1

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Data Index: 672508 (C4 (Web Text))

Max Activating Token Index: 500

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Text #2

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Data Index: 1290509 (C4 (Web Text))

Max Activating Token Index: 413

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Text #3

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Data Index: 387067 (C4 (Web Text))

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Text #4

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Data Index: 31814 (C4 (Web Text))

Max Activating Token Index: 311

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Text #5

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Data Index: 152612 (C4 (Web Text))

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Text #6

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Text #7

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Text #8

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Data Index: 1049010 (C4 (Web Text))

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Text #9

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Data Index: 1244038 (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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Text #14

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Text #15

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Data Index: 1623096 (Python Code)

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Text #16

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Text #17

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Data Index: 491619 (C4 (Web Text))

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Text #18

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Data Index: 170571 (C4 (Web Text))

Max Activating Token Index: 508

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Text #19

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Data Index: 331285 (C4 (Web Text))

Max Activating Token Index: 384

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