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Under Peer Review · Sparse Autoencoders for Pythia-70M-Deduped
Pythia-70M-Deduped
MLP Post
0-MLP-SM
26406
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0-mlp-sm
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Explanations
terms related to specific materials and substances, particularly in the context of science and technology
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
276
+0.16
0.9%
58
+0.13
0.7%
370
+0.12
0.7%
Correlated Neurons
Index
P. Corr.
Cos Sim.
276
+0.16
0.04
370
+0.13
0.03
111
+0.12
0.03
Negative Logits
Īĺ
-2.42
ģ
-2.25
ħ
-2.23
ĭ
-2.20
ĥ½
-2.19
»
-2.12
Ľ
-2.09
¾
-1.99
ī
-1.92
Ħ
-1.92
POSITIVE LOGITS
á̬
1.83
rely
1.80
á̝
1.76
ly
1.63
estly
1.56
alion
1.55
uka
1.49
pity
1.48
burgh
1.48
ening
1.44
Act
ivations
Density 0.076%
Stacked
Snippet
Full
Show Breaks
Hide Breaks
No Known Activations