INDEX

Explanations

specific names and terms related to legal cases or medical precedents

oai_token-act-pair · gpt-4o-mini Triggered by @bot

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GEMMA-2-2B @ 5-gemmascope-res-16k

Configuration

google/gemma-scope-2b-pt-res/layer_5/width_16k/average_l0_68

Prompts (Dashboard)

36,864 prompts, 128 tokens each

Dataset (Dashboard)

monology/pile-uncopyrighted

Features

16,384

Data Type

float32

Hook Name

blocks.5.hook_resid_post

Hook Layer

Architecture

jumprelu

Context Size

1,024

Dataset

monology/pile-uncopyrighted

Activation Function

relu

Embeds

PlotsExplanationShow Test FieldDefault Test Text

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

 Anwar

-0.87

 Crot

-0.86

 Clegg

-0.86

 Huntsville

-0.84

♥♥

-0.83

tenor

-0.82

 đạp

-0.81

 Magdalena

-0.79

Magdalena

-0.79

 Xiong

-0.78

POSITIVE LOGITS

 Hawkins

0.85

’.”

0.79

ReusableCell

0.77

 Rankin

0.77

slu

0.74

bergh

0.74

ţa

0.74

 Meek

0.73

്‍

0.73

 Elgin

0.72

Activations Density 2.805%

specific names and terms related to legal cases or medical precedents

No Comments

No Known Activations