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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    Explanations

    the word 'infographic'

    oai_token-act-pair · gpt-3.5-turbo

    references to visual content, specifically infographics and multimedia formats

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    hood
    -0.89
     Sabha
    -0.82
    gob
    -0.75
    units
    -0.73
    gage
    -0.72
    ties
    -0.72
    ayn
    -0.72
    alties
    -0.70
     neigh
    -0.70
    adesh
    -0.70
    POSITIVE LOGITS
     infographic
    1.08
     Loren
    0.88
    ocument
    0.81
    TED
    0.77
     multimedia
    0.75
     visual
    0.74
     graphic
    0.74
    rodu
    0.69
     Desmond
    0.68
     chore
    0.67
    Activations Density 0.019%

    No Known Activations