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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
7-RES-JB
2072
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MODEL
7-res-jb
Source/SAE
INDEX
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Explanations
numeric values related to data or formatting in a technical context
oai_token-act-pair · gpt-3.5-turbo
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numerical and symbol-based formats, especially in a data or metadata context
oai_token-act-pair · gpt-4o-mini
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New Auto-Interp
AutoInterp Type
claude-4-5-haiku
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Interpretable Score
Intrusion Detection
Top Features by Cosine Similarity
Comparing With
GPT2-SMALL @ 7-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.hook_resid_pre
How To Load
Prompts (Dashboard)
24,576 prompts, 128 tokens each
Dataset (Dashboard)
Skylion007/openwebtext
Features
24,576
Data Type
torch.float32
Hook Point
blocks.7.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
7
Activation Function
relu
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Negative Logits
astroph
-0.69
PRES
-0.68
inj
-0.66
Tec
-0.65
sidelines
-0.65
unders
-0.65
diagn
-0.64
Pres
-0.63
groom
-0.63
asthma
-0.62
POSITIVE LOGITS
2
1.29
3
1.24
ĭ
1.19
ĩ
1.03
ĺ
1.01
1
1.01
4
0.99
Ģ
0.96
ĥ
0.96
2
0.92
Act
ivations
Density 0.152%
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