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

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

Neuron 3 in Layer 2

Load this data into an Interactive Neuroscope

See Documentation here

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



Text #0

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Max Act: 3.2889. Min Act: -0.1700

Data Index: 254193 (C4 (Web Text))

Max Activating Token Index: 632

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Text #1

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Data Index: 823261 (C4 (Web Text))

Max Activating Token Index: 451

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Text #2

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Max Act: 3.1631. Min Act: -0.1700

Data Index: 179320 (C4 (Web Text))

Max Activating Token Index: 521

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Text #3

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Max Act: 3.1316. Min Act: -0.1700

Data Index: 1329792 (C4 (Web Text))

Max Activating Token Index: 913

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Text #4

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Data Index: 740580 (C4 (Web Text))

Max Activating Token Index: 504

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Text #5

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Text #6

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Data Index: 200544 (C4 (Web Text))

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Text #7

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Text #8

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Text #9

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Data Index: 24489 (C4 (Web Text))

Max Activating Token Index: 83

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Text #10

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Text #11

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Text #12

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Text #13

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Data Index: 1405913 (Python Code)

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Text #14

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Text #15

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Data Index: 330850 (C4 (Web Text))

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Text #16

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Text #17

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Text #18

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Data Index: 807385 (C4 (Web Text))

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Text #19

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Data Index: 251736 (C4 (Web Text))

Max Activating Token Index: 255

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