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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

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

Neuron 1960 in Layer 1

Load this data into an Interactive Neuroscope

See Documentation here

Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 3.7869. Min Act: -0.1700

Data Index: 304408 (C4 (Web Text))

Max Activating Token Index: 376

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Text #1

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Max Act: 3.7243. Min Act: -0.1700

Data Index: 824483 (C4 (Web Text))

Max Activating Token Index: 341

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Text #2

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Max Act: 3.7243. Min Act: -0.1700

Data Index: 892975 (C4 (Web Text))

Max Activating Token Index: 909

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Text #3

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Max Act: 3.6930. Min Act: -0.1700

Data Index: 435199 (C4 (Web Text))

Max Activating Token Index: 785

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Text #4

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Data Index: 1291057 (C4 (Web Text))

Max Activating Token Index: 270

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Text #5

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Text #6

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Data Index: 1220717 (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: 317059 (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: 84193 (C4 (Web Text))

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Text #13

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Text #14

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Text #15

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Data Index: 921917 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 68440 (C4 (Web Text))

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Text #18

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Data Index: 1372075 (Python Code)

Max Activating Token Index: 693

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Text #19

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Data Index: 1448219 (Python Code)

Max Activating Token Index: 633

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