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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. 7-RES-JB
    11. 21111
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    INDEX
    Explanations

    mention of specific goals or aims in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    expressions related to the aims or goals of projects and studies

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Solitaire
    -0.71
    Interstitial
    -0.69
    culus
    -0.68
    artifacts
    -0.68
    flush
    -0.63
     Slime
    -0.62
    ilver
    -0.61
    Lot
    -0.60
    cold
    -0.59
    Magic
    -0.58
    POSITIVE LOGITS
     goal
    0.79
    Goal
    0.78
    lessness
    0.71
    orial
    0.70
    iest
    0.70
     Goal
    0.69
     reason
    0.68
    lessly
    0.68
     promoter
    0.67
     lesson
    0.67
    Activations Density 0.113%

    No Known Activations