INDEX

Explanations

followed by names in a sports context, specifically related to soccer

oai_token-act-pair · gpt-3.5-turbo

numerical values or statistics related to player contracts and performances in sports contexts

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

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 6-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.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

 ______

-0.77

Ã±a

-0.76

Ń·

-0.76

heit

-0.73

 ALEC

-0.71

ACS

-0.69

 solic

-0.69

igslist

-0.68

UCS

-0.67

 nonprofits

-0.67

POSITIVE LOGITS

Players

0.99

England

0.99

Football

0.91

Liverpool

0.90

Sport

0.89

Scotland

0.86

 Leicester

0.84

 Bagg

0.83

 Sunderland

0.81

sports

0.81

Activations Density 0.265%

followed by names in a sports context, specifically related to soccer

numerical values or statistics related to player contracts and performances in sports contexts

No Comments

No Known Activations