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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
8-RES-JB
11753
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MODEL
8-res-jb
Source/SAE
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Explanations
sequences related to computer commands or instructions
oai_token-act-pair · gpt-3.5-turbo
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instances of the character "âĢ" which likely signifies an encoding issue or placeholder in the text
oai_token-act-pair · gpt-4o-mini
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Avg Score: 84
New Auto-Interp
AutoInterp Type
claude-4-5-haiku
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Comparing With
GPT2-SMALL @ 8-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
8
Activation Function
relu
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<iframe src="https://www.neuronpedia.org/gpt2-small/8-res-jb/11753?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true" title="Neuronpedia" style="height: 300px; width: 540px;"></iframe>
Link
https://www.neuronpedia.org/gpt2-small/8-res-jb/11753?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
çͰ
-0.78
ãĢIJ
-0.68
Glou
-0.61
sew
-0.61
pastry
-0.61
polyg
-0.59
Syd
-0.59
interf
-0.59
usterity
-0.58
è£ħ
-0.58
POSITIVE LOGITS
Ļ
1.00
¡
0.99
ĺ
0.97
Ĭ
0.95
ľ
0.95
¤
0.94
ĸ
0.93
Ī
0.92
Ń
0.91
ķ
0.90
Act
ivations
Density 0.393%
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