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Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
GPT2-Small
Residual Stream
1-RES-JB
10036
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1-res-jb
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oai_token-act-pair · gpt-3.5-turbo
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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 @ 1-res-jb
Configuration
jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
Architecture
standard
Context Size
128
Dataset
Skylion007/openwebtext
Hook Point Layer
1
Activation Function
relu
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<iframe src="https://www.neuronpedia.org/gpt2-small/1-res-jb/10036?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/1-res-jb/10036?embed=true&embedexplanation=true&embedplots=true&embedsteer=true&embedactivations=true&embedlink=true&embedtest=true
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Negative Logits
»Ĵ
-0.86
Ń·
-0.78
aign
-0.72
charm
-0.70
ĸļ
-0.70
kie
-0.66
ĻĤ
-0.65
asha
-0.63
vain
-0.62
brief
-0.62
POSITIVE LOGITS
],
1.09
...]
1.07
].
1.05
Flavoring
0.88
],
0.88
]
0.86
]
0.83
][
0.80
]:
0.80
']
0.80
Act
ivations
Density 0.013%
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