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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 2004 in Layer 0

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

Max Range: 3.0322. Min Range: -3.0322

Max Act: 3.0322. Min Act: -0.1700

Data Index: 1504651 (Python Code)

Max Activating Token Index: 74

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Text #1

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Max Act: 2.9373. Min Act: -0.1700

Data Index: 1546819 (Python Code)

Max Activating Token Index: 330

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Text #2

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Max Act: 2.9215. Min Act: -0.1700

Data Index: 1380141 (Python Code)

Max Activating Token Index: 165

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Text #3

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Max Act: 2.8897. Min Act: -0.1700

Data Index: 1387073 (Python Code)

Max Activating Token Index: 323

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Text #4

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Max Act: 2.9215. Min Act: -0.1700

Data Index: 1360792 (Python Code)

Max Activating Token Index: 571

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Text #5

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Data Index: 1631039 (Python Code)

Max Activating Token Index: 228

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Data Index: 1468762 (Python Code)

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Text #7

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Data Index: 1653722 (Python Code)

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Text #8

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Data Index: 1600998 (Python Code)

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Text #9

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Data Index: 1368068 (Python Code)

Max Activating Token Index: 766

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Text #10

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Data Index: 1436830 (Python Code)

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Text #11

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Data Index: 1361770 (Python Code)

Max Activating Token Index: 606

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Text #12

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Data Index: 1402895 (Python Code)

Max Activating Token Index: 375

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Text #13

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Data Index: 1438571 (Python Code)

Max Activating Token Index: 701

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Text #14

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Data Index: 1600133 (Python Code)

Max Activating Token Index: 626

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Text #15

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Data Index: 1519731 (Python Code)

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Text #16

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Text #17

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Data Index: 1573658 (Python Code)

Max Activating Token Index: 880

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Text #18

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Data Index: 1565557 (Python Code)

Max Activating Token Index: 509

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Text #19

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Data Index: 1374430 (Python Code)

Max Activating Token Index: 290

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