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Under Peer Review · Sparse Autoencoders for Pythia-70M-Deduped
Pythia-70M-Deduped
MLP Post
0-MLP-SM
26413
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MODEL
0-mlp-sm
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Explanations
references to legal proceedings or court-related terminology
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
Configuration
ctigges/pythia-70m-deduped__mlp-sm_processed/0-mlp-sm
How To Load
Prompts (Dashboard)
32,768 prompts, 128 tokens each
Dataset (Dashboard)
monology/pile-uncopyrighted
Features
32,768
Data Type
torch.float32
Hook Name
blocks.0.hook_mlp_out
Hook Layer
0
Architecture
standard
Context Size
128
Dataset
EleutherAI/the_pile_deduplicated
Activation Function
relu
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Neuron Alignment
Index
Value
% of L₁
48
+0.13
0.7%
321
+0.11
0.6%
53
+0.11
0.6%
Correlated Neurons
Index
P. Corr.
Cos Sim.
48
+0.13
0.02
35
+0.11
0.02
322
+0.11
0.02
Negative Logits
omycin
-1.71
\.
-1.65
-1.57
.^[@
-1.54
opposed
-1.54
ically
-1.50
](
-1.46
-1.45
-1.45
-1.45
POSITIVE LOGITS
Ī
1.62
sed
1.61
¿
1.42
stanbul
1.41
speech
1.40
$-
1.40
bachelor
1.40
vous
1.39
iors
1.38
↵
1.37
Act
ivations
Density 0.162%
Stacked
Snippet
Full
Show Breaks
Hide Breaks
No Known Activations