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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
    11. 5564
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    Explanations

    terms related to achieving objectives or targets

    oai_token-act-pair · gpt-3.5-turbo

    references to goals and scoring

    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
    colo
    -0.81
    vette
    -0.81
    çĦ
    -0.73
    ç¥ŀ
    -0.71
     Debor
    -0.70
    cox
    -0.69
    umbn
    -0.68
     jaws
    -0.67
    abus
    -0.66
    autical
    -0.66
    POSITIVE LOGITS
     Goal
    1.07
    Goal
    0.88
    keepers
    0.85
     goalkeeper
    0.80
     Goals
    0.79
    keeper
    0.78
     Programme
    0.77
    ":["
    0.72
    aye
    0.72
     goalie
    0.70
    Activations Density 0.009%

    No Known Activations