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

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

Neuron 2001 in Layer 1

Load this data into an Interactive Neuroscope

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



Text #0

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Max Act: 4.3858. Min Act: -0.1700

Data Index: 1589877 (Python Code)

Max Activating Token Index: 330

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Text #1

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Max Act: 4.2608. Min Act: -0.1700

Data Index: 1383205 (Python Code)

Max Activating Token Index: 353

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Text #2

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Max Act: 4.2608. Min Act: -0.1700

Data Index: 1548495 (Python Code)

Max Activating Token Index: 812

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Text #3

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Max Act: 4.1983. Min Act: -0.1700

Data Index: 1302408 (C4 (Web Text))

Max Activating Token Index: 915

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Text #4

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Data Index: 1414266 (Python Code)

Max Activating Token Index: 183

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Text #5

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Data Index: 898256 (C4 (Web Text))

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Text #6

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Data Index: 1617178 (Python Code)

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Text #7

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Data Index: 721621 (C4 (Web Text))

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Text #8

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Data Index: 307830 (C4 (Web Text))

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Text #9

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Data Index: 1342905 (C4 (Web Text))

Max Activating Token Index: 54

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Text #10

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Data Index: 1004153 (C4 (Web Text))

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Text #11

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Data Index: 884730 (C4 (Web Text))

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Text #12

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Data Index: 305765 (C4 (Web Text))

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Text #13

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Data Index: 1527394 (Python Code)

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Text #14

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Data Index: 1053284 (C4 (Web Text))

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Text #15

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Data Index: 1154205 (C4 (Web Text))

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Text #16

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Data Index: 237140 (C4 (Web Text))

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Text #17

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Data Index: 693308 (C4 (Web Text))

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Text #18

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Data Index: 279413 (C4 (Web Text))

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Text #19

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Data Index: 767081 (C4 (Web Text))

Max Activating Token Index: 990

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