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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. 3-RES-JB
    11. 6229
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    Explanations

    references to specific sports teams and related activities

    oai_token-act-pair · gpt-3.5-turbo

    mentions of specific football teams and players

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Anonymous
    -0.85
     Zup
    -0.77
    ospons
    -0.77
    enegger
    -0.76
    ertodd
    -0.75
    chrom
    -0.75
    toggle
    -0.74
    {"
    -0.73
    soType
    -0.73
    renheit
    -0.72
    POSITIVE LOGITS
     goalkeeper
    1.09
     Wolves
    1.08
     striker
    1.08
     midfielder
    1.04
     Football
    1.03
     footballer
    1.03
     FC
    1.02
     winger
    0.99
     defences
    0.98
     youngster
    0.96
    Activations Density 0.152%

    No Known Activations