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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. 9808
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    INDEX
    Explanations

    quantitative measurements, specifically percentages or points

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to percentage points and polling results

    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
    ufact
    -0.72
    rology
    -0.70
    lict
    -0.69
    uthor
    -0.68
    ourt
    -0.68
    rodu
    -0.67
     Tycoon
    -0.66
    ffic
    -0.63
    cules
    -0.62
    ework
    -0.62
    POSITIVE LOGITS
     apiece
    0.84
    point
    0.84
    hift
    0.82
    lash
    0.80
    manship
    0.75
     (+
    0.74
    */(
    0.71
     increments
    0.71
     (-
    0.70
    points
    0.70
    Activations Density 0.017%

    No Known Activations