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

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

Neuron 1295 in Layer 3

Load this data into an Interactive Neuroscope

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



Text #0

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Max Act: 4.3635. Min Act: -0.1700

Data Index: 1387700 (Python Code)

Max Activating Token Index: 759

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Text #1

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Max Act: 4.2697. Min Act: -0.1700

Data Index: 427644 (C4 (Web Text))

Max Activating Token Index: 355

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Text #2

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Max Act: 4.2072. Min Act: -0.1700

Data Index: 381629 (C4 (Web Text))

Max Activating Token Index: 948

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Text #3

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Max Act: 4.2385. Min Act: -0.1700

Data Index: 1356324 (C4 (Web Text))

Max Activating Token Index: 903

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Text #4

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Data Index: 772208 (C4 (Web Text))

Max Activating Token Index: 855

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Text #5

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Text #6

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Data Index: 1362629 (Python Code)

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Text #7

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Data Index: 1068413 (C4 (Web Text))

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Text #8

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Data Index: 858538 (C4 (Web Text))

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Text #9

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Data Index: 1294649 (C4 (Web Text))

Max Activating Token Index: 548

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Text #10

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Data Index: 1186403 (C4 (Web Text))

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Text #11

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Text #12

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Text #13

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Data Index: 365956 (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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Text #17

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Data Index: 792058 (C4 (Web Text))

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Text #18

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Data Index: 41282 (C4 (Web Text))

Max Activating Token Index: 202

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Text #19

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Data Index: 826123 (C4 (Web Text))

Max Activating Token Index: 462

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