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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. 17672
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    INDEX
    Explanations

    quantitative terms emphasizing amounts or numbers

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "quantity" in various contexts

    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
    stal
    -0.65
    boa
    -0.65
    inav
    -0.65
    gotten
    -0.62
    lez
    -0.62
     namesake
    -0.61
    INA
    -0.61
     Cosponsors
    -0.60
    ODE
    -0.60
     Vikings
    -0.60
    POSITIVE LOGITS
     quantity
    1.12
     quantities
    1.02
    itatively
    0.91
    Quantity
    0.88
    quant
    0.86
    ickr
    0.81
    odynam
    0.81
     quotas
    0.76
     thereof
    0.76
     ILCS
    0.75
    Activations Density 0.013%

    No Known Activations