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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 9-RES-JB
    11. 8953
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    Explanations

    mentions of specific football/soccer teams

    oai_token-act-pair · gpt-3.5-turbo

    mentions of football clubs and their related contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.hook_resid_pre
    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
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Zup
    -0.95
     Ples
    -0.84
    Els
    -0.78
    TED
    -0.78
     Navajo
    -0.73
    oard
    -0.73
     Twain
    -0.73
    ãĥł
    -0.72
     Cherokee
    -0.72
    ngth
    -0.72
    POSITIVE LOGITS
     Football
    1.18
     midfielder
    1.16
     FC
    1.15
     goalkeeper
    1.10
     winger
    1.05
     footballer
    1.03
     striker
    1.02
     Athletic
    1.01
     Hots
    1.01
     youngster
    0.96
    Activations Density 0.169%

    No Known Activations