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Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 2015 in Layer 0

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')



Text #0

Max Range: 2.8727. Min Range: -2.8727

Max Act: 2.8727. Min Act: -0.1700

Data Index: 1513269 (Python Code)

Max Activating Token Index: 496

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Text #1

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Max Act: 2.8727. Min Act: -0.1700

Data Index: 1376826 (Python Code)

Max Activating Token Index: 593

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Text #2

Max Range: 2.8727. Min Range: -2.8727

Max Act: 2.8409. Min Act: -0.1700

Data Index: 914779 (C4 (Web Text))

Max Activating Token Index: 866

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Text #3

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Max Act: 2.8409. Min Act: -0.1700

Data Index: 1461534 (Python Code)

Max Activating Token Index: 171

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Text #4

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Max Act: 2.8250. Min Act: -0.1700

Data Index: 1121785 (C4 (Web Text))

Max Activating Token Index: 229

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Text #5

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Data Index: 1546261 (Python Code)

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Data Index: 1369881 (Python Code)

Max Activating Token Index: 576

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Text #7

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Data Index: 1559015 (Python Code)

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Text #8

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Data Index: 1544613 (Python Code)

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Text #9

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Data Index: 1631069 (Python Code)

Max Activating Token Index: 848

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Text #10

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Data Index: 1486753 (Python Code)

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Text #11

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Data Index: 1365518 (Python Code)

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Data Index: 1475280 (Python Code)

Max Activating Token Index: 657

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Text #13

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Data Index: 591847 (C4 (Web Text))

Max Activating Token Index: 213

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Text #14

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Data Index: 1587670 (Python Code)

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Text #15

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Data Index: 1460102 (Python Code)

Max Activating Token Index: 538

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Text #16

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Text #17

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Data Index: 1611922 (Python Code)

Max Activating Token Index: 327

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Text #18

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Data Index: 1426832 (Python Code)

Max Activating Token Index: 491

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Text #19

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Data Index: 1638897 (Python Code)

Max Activating Token Index: 611

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