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Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 2009 in Layer 1

Load this data into an Interactive Neuroscope

See Documentation here

Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')



Text #0

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Max Act: 5.6979. Min Act: -0.1700

Data Index: 113549 (C4 (Web Text))

Max Activating Token Index: 105

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Text #1

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Data Index: 1264250 (C4 (Web Text))

Max Activating Token Index: 215

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Text #2

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Max Act: 5.6666. Min Act: -0.1700

Data Index: 751567 (C4 (Web Text))

Max Activating Token Index: 259

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Text #3

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Data Index: 939023 (C4 (Web Text))

Max Activating Token Index: 175

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Text #4

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Data Index: 594636 (C4 (Web Text))

Max Activating Token Index: 208

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Text #5

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Data Index: 66368 (C4 (Web Text))

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Text #6

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Data Index: 985047 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1228282 (C4 (Web Text))

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Text #9

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Data Index: 336189 (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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Data Index: 1028625 (C4 (Web Text))

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Text #13

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Data Index: 472652 (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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Data Index: 472908 (C4 (Web Text))

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Text #18

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Text #19

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Data Index: 533055 (C4 (Web Text))

Max Activating Token Index: 315

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