INDEX

Explanations

phrases related to specific names and medical terms

oai_token-act-pair · gpt-3.5-turbo

specific names or acronyms related to organizations, medical terms, or regulatory bodies

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

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 4-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.hook_resid_pre

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

Skylion007/openwebtext

Features

24,576

Data Type

torch.float32

Hook Point

blocks.4.hook_resid_pre

Architecture

standard

Context Size

128

Dataset

Skylion007/openwebtext

Hook Point Layer

Activation Function

relu

Embeds

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

 Wick

-0.71

apo

-0.69

des

-0.65

hani

-0.65

rike

-0.65

Boh

-0.64

 sciences

-0.63

need

-0.63

rians

-0.61

 Rover

-0.61

POSITIVE LOGITS

OPA

0.97

etsk

0.93

merce

0.90

yright

0.89

phrine

0.87

vernment

0.86

olicy

0.85

ACA

0.85

odcast

0.84

mercial

0.79

Activations Density 0.012%

phrases related to specific names and medical terms

specific names or acronyms related to organizations, medical terms, or regulatory bodies

No Comments

No Known Activations