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Model: GELU Model: 4 Layers, 2048 Neurons per Layer

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

Neuron 24 in Layer 2

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

Max Range: 4.2754. Min Range: -4.2754

Max Act: 4.2754. Min Act: -0.1700

Data Index: 1273274 (C4 (Web Text))

Max Activating Token Index: 445

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Text #1

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Max Act: 4.1816. Min Act: -0.1700

Data Index: 116031 (C4 (Web Text))

Max Activating Token Index: 517

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Text #2

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Max Act: 4.1191. Min Act: -0.1700

Data Index: 941406 (C4 (Web Text))

Max Activating Token Index: 643

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Text #3

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Max Act: 4.1191. Min Act: -0.1700

Data Index: 96507 (C4 (Web Text))

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Text #4

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Data Index: 792936 (C4 (Web Text))

Max Activating Token Index: 519

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Text #5

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Data Index: 986152 (C4 (Web Text))

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Text #6

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Data Index: 662776 (C4 (Web Text))

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Text #7

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Text #8

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Max Act: 4.1191. Min Act: -0.1700

Data Index: 1118115 (C4 (Web Text))

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Text #9

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Data Index: 1013635 (C4 (Web Text))

Max Activating Token Index: 789

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Text #10

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Data Index: 998333 (C4 (Web Text))

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Truncated

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Text #11

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Text #12

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Data Index: 1198734 (C4 (Web Text))

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Text #13

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Data Index: 1124457 (C4 (Web Text))

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Text #14

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Text #15

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Text #16

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Data Index: 646452 (C4 (Web Text))

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Text #17

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Data Index: 1134437 (C4 (Web Text))

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Text #18

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Data Index: 1140253 (C4 (Web Text))

Max Activating Token Index: 366

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Text #19

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Data Index: 1155791 (C4 (Web Text))

Max Activating Token Index: 439

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