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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. 15958
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    Explanations

    statistical information related to sports, specifically focusing on the performance of players in terms of points and rebounds

    oai_token-act-pair · gpt-3.5-turbo

    terms related to basketball rebounds and rebound statistics

    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
    cas
    -0.77
    cho
    -0.69
    âĸ¬âĸ¬
    -0.62
    FAULT
    -0.62
    non
    -0.60
    ige
    -0.60
    OPA
    -0.59
    gemony
    -0.58
     Pall
    -0.58
     Anglo
    -0.57
    POSITIVE LOGITS
     rebounds
    1.02
    oppable
    0.83
    esome
    0.80
    halla
    0.79
    itzer
    0.79
    hots
    0.79
    pointers
    0.75
    ilion
    0.74
    olars
    0.73
    interstitial
    0.71
    Activations Density 0.020%

    No Known Activations