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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. 4-RES-JB
    11. 4343
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    Explanations

    quantitative information related to units, barrels, and copies in different contexts

    oai_token-act-pair · gpt-3.5-turbo

    quantitative measures related to units sold, barrels produced, and inventory levels

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

    No Comments

    Negative Logits
    redo
    -0.64
     shell
    -0.63
    kefeller
    -0.61
     Archer
    -0.61
     Vice
    -0.59
     Dod
    -0.56
     Neo
    -0.56
     McCl
    -0.55
     corpor
    -0.55
    neum
    -0.54
    POSITIVE LOGITS
    poons
    1.13
     apiece
    0.97
    omething
    0.95
    pace
    0.88
    paces
    0.87
    awatts
    0.80
    abytes
    0.78
    afety
    0.76
     per
    0.74
    illion
    0.73
    Activations Density 0.172%

    No Known Activations