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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
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    Explanations

    mentions of frogs

    oai_token-act-pair · gpt-3.5-turbo

    references to frogs and amphibians

    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
     Chamberlain
    -0.72
     Hemp
    -0.67
     Goods
    -0.66
    QUIRE
    -0.66
    Interstitial
    -0.65
    ATES
    -0.61
    ×ij
    -0.61
     concess
    -0.58
     Palestin
    -0.58
     combust
    -0.57
    POSITIVE LOGITS
    grass
    1.06
    lings
    1.02
    frog
    0.93
    fish
    0.93
     frogs
    0.90
    mons
    0.88
    weed
    0.87
     frog
    0.83
    tailed
    0.82
    adier
    0.82
    Activations Density 0.015%

    No Known Activations