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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. 19637
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    Explanations

    references to players playing for specific sports teams

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating participation or involvement in activities or events

    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
     FOIA
    -0.85
    aminer
    -0.76
    soDeliveryDate
    -0.75
    issues
    -0.73
     solicitation
    -0.73
    inventoryQuantity
    -0.73
    License
    -0.70
     sourced
    -0.68
    pmwiki
    -0.68
    Driver
    -0.68
    POSITIVE LOGITS
     Team
    0.97
     England
    0.97
     Wolver
    0.95
     teammates
    0.94
     Teams
    0.93
     Tigers
    0.92
     teams
    0.91
     Sunderland
    0.91
     Wildcats
    0.90
     Argentina
    0.90
    Activations Density 0.142%

    No Known Activations