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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
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    INDEX
    Explanations

    quantitative measurements or analyses

    oai_token-act-pair · gpt-3.5-turbo

    terms related to quantitative analysis

    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
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    No Comments

    Negative Logits
    HOME
    -0.88
     Archdemon
    -0.70
     Mansion
    -0.67
     Spit
    -0.64
     Tycoon
    -0.64
    lihood
    -0.63
    LAND
    -0.63
     Mistress
    -0.63
     blades
    -0.62
     Kirin
    -0.62
    POSITIVE LOGITS
    itatively
    1.40
     quant
    1.23
    imet
    0.97
    ifiable
    0.96
    eros
    0.87
    quant
    0.86
    idian
    0.86
     quantify
    0.82
    tarians
    0.82
    ifies
    0.81
    Activations Density 0.014%

    No Known Activations