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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. 9-RES-JB
    11. 16519
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    Explanations

    information related to acquisitions - both the act of acquiring and the items being acquired

    oai_token-act-pair · gpt-3.5-turbo

    terms related to obtaining or gaining possession of items or entities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    acea
    -0.95
    hov
    -0.89
    dayName
    -0.75
    heet
    -0.73
    atever
    -0.72
    eday
    -0.71
    jab
    -0.69
    ocrine
    -0.69
    icho
    -0.69
    erella
    -0.68
    POSITIVE LOGITS
    ments
    0.86
    ader
    0.72
    ment
    0.72
    rification
    0.71
     trophies
    0.68
    DAQ
    0.68
    isitions
    0.65
     rights
    0.65
    MENTS
    0.63
     holdings
    0.62
    Activations Density 0.042%

    No Known Activations