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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. 2-RES-JB
    11. 13435
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    Explanations

    phrases related to preparing or preheating for an activity or event

    oai_token-act-pair · gpt-3.5-turbo

    terms related to preparation processes, particularly in cooking or planning

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    ANA
    -0.71
    Spider
    -0.71
    ĸļ
    -0.70
     Reporter
    -0.68
    worms
    -0.66
    ãĥīãĥ©ãĤ´ãĥ³
    -0.65
     breath
    -0.65
    berg
    -0.64
     depths
    -0.63
     Bee
    -0.62
    POSITIVE LOGITS
    ruary
    0.78
    requisites
    0.77
    isites
    0.76
    aphael
    0.76
    arers
    0.74
    icipated
    0.73
    autions
    0.73
    ilial
    0.73
    requisite
    0.73
    istration
    0.72
    Activations Density 0.089%

    No Known Activations