INDEX

Explanations

names of individuals involved in legal or criminal activities

oai_token-act-pair · gpt-3.5-turbo

instances of the verb "was" indicating past actions or events

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

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 3-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.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

inav

-0.65

 Which

-0.65

 Millions

-0.63

 Telesc

-0.61

 invocation

-0.60

 Extend

-0.60

 Solution

-0.60

Footnote

-0.59

Make

-0.58

ological

-0.58

POSITIVE LOGITS

nt

1.01

hes

0.98

 supposed

0.94

 able

0.91

wolves

0.90

wolf

0.89

 deemed

0.88

hers

0.86

 born

0.85

 definitely

0.84

Activations Density 0.489%

names of individuals involved in legal or criminal activities

instances of the verb "was" indicating past actions or events

No Comments

No Known Activations