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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. 6-RES-JB
    11. 13590
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    INDEX
    Explanations

    phrases related to visual fixation or intense gaze

    oai_token-act-pair · gpt-3.5-turbo

    actions related to looking or observing

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inventoryQuantity
    -0.78
    ctr
    -0.71
    interstitial
    -0.69
    notes
    -0.67
    rosse
    -0.67
    ERN
    -0.66
    actionDate
    -0.65
    icult
    -0.64
    akuya
    -0.62
    STRUCT
    -0.61
    POSITIVE LOGITS
     dag
    0.95
     gaze
    0.94
     stares
    0.93
     stare
    0.91
     staring
    0.89
     blank
    0.89
     stared
    0.80
    creen
    0.75
     gazing
    0.75
     unfocused
    0.74
    Activations Density 0.024%

    No Known Activations