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

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

Neuron 46 in Layer 2

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: 5.0145. Min Act: -0.1700

Data Index: 755372 (C4 (Web Text))

Max Activating Token Index: 695

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Text #1

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Data Index: 1343324 (C4 (Web Text))

Max Activating Token Index: 1005

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Text #2

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Max Act: 4.9207. Min Act: -0.1700

Data Index: 1065841 (C4 (Web Text))

Max Activating Token Index: 683

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Text #3

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Data Index: 878440 (C4 (Web Text))

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Text #4

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Data Index: 100297 (C4 (Web Text))

Max Activating Token Index: 518

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Text #6

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Data Index: 1344237 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 870336 (C4 (Web Text))

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Text #9

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Data Index: 411944 (C4 (Web Text))

Max Activating Token Index: 970

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Text #10

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Data Index: 934347 (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: 630201 (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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Text #18

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Data Index: 837466 (C4 (Web Text))

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Text #19

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Data Index: 1096601 (C4 (Web Text))

Max Activating Token Index: 49

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