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

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

Neuron 1922 in Layer 2

Load this data into an Interactive Neuroscope

See Documentation here

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



Text #0

Max Range: 4.3640. Min Range: -4.3640

Max Act: 4.3640. Min Act: -0.1700

Data Index: 1514175 (Python Code)

Max Activating Token Index: 835

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Text #1

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Max Act: 4.1765. Min Act: -0.1700

Data Index: 1273556 (C4 (Web Text))

Max Activating Token Index: 760

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Text #2

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Max Act: 4.1140. Min Act: -0.1700

Data Index: 1556637 (Python Code)

Max Activating Token Index: 597

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Text #3

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Max Act: 4.0827. Min Act: -0.1700

Data Index: 678115 (C4 (Web Text))

Max Activating Token Index: 189

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Text #4

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Max Act: 4.0514. Min Act: -0.1700

Data Index: 1570119 (Python Code)

Max Activating Token Index: 415

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Text #5

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Data Index: 1384043 (Python Code)

Max Activating Token Index: 733

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Text #6

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Data Index: 1481253 (Python Code)

Max Activating Token Index: 716

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Text #7

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Data Index: 1598388 (Python Code)

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Text #8

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Data Index: 1398320 (Python Code)

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Text #9

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Data Index: 1607072 (Python Code)

Max Activating Token Index: 384

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Text #10

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Data Index: 1453974 (Python Code)

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Text #11

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Data Index: 1581735 (Python Code)

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Text #12

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Data Index: 1447413 (Python Code)

Max Activating Token Index: 457

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Text #13

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Data Index: 1369883 (Python Code)

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Text #14

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Data Index: 1436980 (Python Code)

Max Activating Token Index: 381

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Text #15

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Data Index: 1462735 (Python Code)

Max Activating Token Index: 454

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Text #16

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Text #17

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Data Index: 1426863 (Python Code)

Max Activating Token Index: 555

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Text #18

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Data Index: 1527951 (Python Code)

Max Activating Token Index: 667

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Text #19

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Data Index: 1616059 (Python Code)

Max Activating Token Index: 463

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