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

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

Neuron 1460 in Layer 2

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: 4.6234. Min Act: -0.1700

Data Index: 359918 (C4 (Web Text))

Max Activating Token Index: 487

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Text #1

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Max Act: 4.5922. Min Act: -0.1700

Data Index: 836686 (C4 (Web Text))

Max Activating Token Index: 864

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Text #2

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Max Act: 4.5609. Min Act: -0.1700

Data Index: 1512314 (Python Code)

Max Activating Token Index: 11

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Text #3

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Data Index: 1376441 (Python Code)

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Text #4

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Data Index: 854235 (C4 (Web Text))

Max Activating Token Index: 847

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Text #5

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Data Index: 96171 (C4 (Web Text))

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Text #6

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Data Index: 1139922 (C4 (Web Text))

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Text #7

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Data Index: 332333 (C4 (Web Text))

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Text #8

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Data Index: 282510 (C4 (Web Text))

Max Activating Token Index: 698

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Text #9

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Data Index: 977810 (C4 (Web Text))

Max Activating Token Index: 943

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Text #10

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Text #11

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Text #12

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Data Index: 870493 (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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Text #16

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Data Index: 168542 (C4 (Web Text))

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Text #17

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Data Index: 879403 (C4 (Web Text))

Max Activating Token Index: 803

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Text #18

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Max Act: 4.4672. Min Act: -0.1700

Data Index: 74703 (C4 (Web Text))

Max Activating Token Index: 568

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Text #19

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Data Index: 451870 (C4 (Web Text))

Max Activating Token Index: 490

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