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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
9-RES-JB
4350
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9-res-jb
Source/SAE
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Explanations
numerical codes or technical specifications
oai_token-act-pair · gpt-3.5-turbo
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numerical values and specific identifiers related to data metrics
oai_token-act-pair · gpt-4o-mini
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New Auto-Interp
AutoInterp Type
claude-4-5-haiku
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Top Features by Cosine Similarity
Comparing With
GPT2-SMALL @ 9-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
9
Activation Function
relu
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https://www.neuronpedia.org/gpt2-small/9-res-jb/4350?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
di
-0.84
Dixon
-0.80
261
-0.75
iph
-0.73
OD
-0.73
rh
-0.73
IB
-0.72
inth
-0.72
iosis
-0.72
DI
-0.71
POSITIVE LOGITS
00
1.05
Į
0.95
->
0.95
->
0.90
005
0.86
":["
0.84
-->
0.84
aler
0.82
004
0.81
IJ
0.81
Act
ivations
Density 0.373%
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