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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. 2-RES-JB
    11. 11358
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    Explanations

    references to specific locations, particularly Monte Carlo and Monaco

    oai_token-act-pair · gpt-3.5-turbo

    references to the location "Monte" and its various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    hips
    -0.74
    irlf
    -0.73
    oppable
    -0.71
    hip
    -0.70
    ¿
    -0.70
    inyl
    -0.70
    inventoryQuantity
    -0.70
    Marginal
    -0.69
    ivities
    -0.68
    inning
    -0.64
    POSITIVE LOGITS
     Monte
    1.11
     Carlo
    0.92
    ucci
    0.91
    folios
    0.89
    fort
    0.83
    erey
    0.81
    bris
    0.78
    quist
    0.78
    folio
    0.77
    mont
    0.77
    Activations Density 0.006%

    No Known Activations