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

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

Neuron 5 in Layer 3

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: 5.0286. Min Act: -0.1700

Data Index: 1355986 (C4 (Web Text))

Max Activating Token Index: 613

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Text #1

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Max Act: 4.9974. Min Act: -0.1700

Data Index: 919364 (C4 (Web Text))

Max Activating Token Index: 116

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Text #2

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Max Act: 5.0286. Min Act: -0.1700

Data Index: 179383 (C4 (Web Text))

Max Activating Token Index: 497

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Text #3

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Max Act: 4.9349. Min Act: -0.1700

Data Index: 545961 (C4 (Web Text))

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Text #4

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Data Index: 459927 (C4 (Web Text))

Max Activating Token Index: 237

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Text #5

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Data Index: 580716 (C4 (Web Text))

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Text #6

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Data Index: 1625812 (Python Code)

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Text #7

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Text #8

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Data Index: 159550 (C4 (Web Text))

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Text #9

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Data Index: 132286 (C4 (Web Text))

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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: 407791 (C4 (Web Text))

Max Activating Token Index: 951

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Text #14

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Text #15

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Data Index: 249018 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 4382 (C4 (Web Text))

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Text #18

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Data Index: 360803 (C4 (Web Text))

Max Activating Token Index: 118

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Text #19

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Data Index: 740587 (C4 (Web Text))

Max Activating Token Index: 107

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