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

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

Neuron 205 in Layer 1

Load this data into an Interactive Neuroscope

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



Text #0

Max Range: 4.2135. Min Range: -4.2135

Max Act: 4.2135. Min Act: -0.1700

Data Index: 1282356 (C4 (Web Text))

Max Activating Token Index: 208

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Text #1

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Max Act: 4.1041. Min Act: -0.1670

Data Index: 1136465 (C4 (Web Text))

Max Activating Token Index: 629

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Text #2

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Max Act: 4.1197. Min Act: -0.1700

Data Index: 1315322 (C4 (Web Text))

Max Activating Token Index: 782

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Text #3

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Max Act: 4.0885. Min Act: -0.1700

Data Index: 271845 (C4 (Web Text))

Max Activating Token Index: 948

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Text #4

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Data Index: 1126290 (C4 (Web Text))

Max Activating Token Index: 135

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Text #5

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Data Index: 1511846 (Python Code)

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Text #6

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Data Index: 98578 (C4 (Web Text))

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Text #7

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Data Index: 903944 (C4 (Web Text))

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Text #8

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Data Index: 638575 (C4 (Web Text))

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Text #9

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Data Index: 175708 (C4 (Web Text))

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Text #10

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Data Index: 1078154 (C4 (Web Text))

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Text #11

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Text #12

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Data Index: 1560997 (Python Code)

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Text #13

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Data Index: 1276250 (C4 (Web Text))

Max Activating Token Index: 909

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Text #14

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Text #15

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Data Index: 1144654 (C4 (Web Text))

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Text #16

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Data Index: 1150018 (C4 (Web Text))

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Text #17

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Data Index: 179725 (C4 (Web Text))

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Text #18

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Max Act: 3.8852. Min Act: -0.1700

Data Index: 298101 (C4 (Web Text))

Max Activating Token Index: 1001

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Text #19

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Data Index: 1099343 (C4 (Web Text))

Max Activating Token Index: 357

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