INDEX

Explanations

specific types of entities associated with criminal activities

oai_token-act-pair · gpt-3.5-turbo Triggered by @bot

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 8-res_fs24576-jb

Configuration

jbloom/GPT2-Small-Feature-Splitting-Experiment-Layer-8/blocks.8.hook_resid_pre_24576

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

Skylion007/openwebtext

Features

24,576

Data Type

torch.float32

Hook Point

blocks.8.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

issors

-0.76

ãĥ¼ãĥĨ

-0.70

 chains

-0.65

 Chain

-0.64

ãĥ¼ãĥĨãĤ£

-0.58

 chain

-0.57

 consolidation

-0.57

pread

-0.57

EVA

-0.57

etts

-0.56

POSITIVE LOGITS

urnal

1.12

mber

0.71

agon

0.68

hawk

0.67

EMBER

0.66

heim

0.65

manship

0.65

oso

0.65

omi

0.65

agraph

0.64

Activations Density 0.053%

specific types of entities associated with criminal activities

No Comments

No Known Activations