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

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

Neuron 2 in Layer 3

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: 5.9507. Min Act: -0.1700

Data Index: 29280 (C4 (Web Text))

Max Activating Token Index: 305

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Text #1

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Data Index: 1263693 (C4 (Web Text))

Max Activating Token Index: 42

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Text #2

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Max Act: 5.8882. Min Act: -0.1700

Data Index: 605114 (C4 (Web Text))

Max Activating Token Index: 176

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Text #3

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Max Act: 5.7944. Min Act: -0.1700

Data Index: 269568 (C4 (Web Text))

Max Activating Token Index: 855

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Text #4

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Max Act: 5.7319. Min Act: -0.1700

Data Index: 262703 (C4 (Web Text))

Max Activating Token Index: 1016

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Text #5

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Data Index: 477012 (C4 (Web Text))

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Text #6

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Data Index: 653020 (C4 (Web Text))

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Text #7

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Data Index: 1337329 (C4 (Web Text))

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Text #8

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Data Index: 174953 (C4 (Web Text))

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Text #9

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Data Index: 193758 (C4 (Web Text))

Max Activating Token Index: 1002

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Text #10

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Text #11

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Text #12

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Data Index: 1167988 (C4 (Web Text))

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Text #13

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Data Index: 686520 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 171202 (C4 (Web Text))

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Text #16

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Data Index: 120695 (C4 (Web Text))

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Text #17

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Data Index: 1092257 (C4 (Web Text))

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Text #18

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Data Index: 815690 (C4 (Web Text))

Max Activating Token Index: 296

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Text #19

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Data Index: 809824 (C4 (Web Text))

Max Activating Token Index: 860

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