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

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

Neuron 1876 in Layer 1

Load this data into an Interactive Neuroscope

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



Text #0

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Max Act: 3.3267. Min Act: -0.1700

Data Index: 1479361 (Python Code)

Max Activating Token Index: 229

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Text #1

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Max Act: 3.3424. Min Act: -0.1700

Data Index: 1612187 (Python Code)

Max Activating Token Index: 574

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Text #2

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Max Act: 3.2796. Min Act: -0.1700

Data Index: 1426513 (Python Code)

Max Activating Token Index: 978

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Text #3

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Max Act: 3.2010. Min Act: -0.1700

Data Index: 1522732 (Python Code)

Max Activating Token Index: 503

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Text #4

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Data Index: 1596447 (Python Code)

Max Activating Token Index: 545

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Text #5

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Data Index: 1635474 (Python Code)

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Text #6

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Data Index: 1625045 (Python Code)

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Text #7

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Data Index: 1586173 (Python Code)

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Text #8

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Data Index: 1477233 (Python Code)

Max Activating Token Index: 215

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Text #9

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Data Index: 1391113 (Python Code)

Max Activating Token Index: 962

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Text #10

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Data Index: 1605412 (Python Code)

Max Activating Token Index: 338

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Text #11

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Data Index: 1653485 (Python Code)

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Text #12

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Data Index: 1369032 (Python Code)

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Text #13

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Data Index: 1436703 (Python Code)

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Text #14

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Data Index: 1441630 (Python Code)

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Text #15

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Text #16

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Data Index: 401078 (C4 (Web Text))

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Text #17

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Data Index: 1469406 (Python Code)

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Text #18

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Max Act: 3.0434. Min Act: -0.1700

Data Index: 1189138 (C4 (Web Text))

Max Activating Token Index: 777

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Text #19

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Data Index: 1476270 (Python Code)

Max Activating Token Index: 891

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