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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    references to bottled water and canned food items

    oai_token-act-pair · gpt-3.5-turbo

    references to bottled and canned food products

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    nesota
    -0.86
    lihood
    -0.82
    rn
    -0.79
    ffield
    -0.76
    lde
    -0.76
    ĪĴ
    -0.76
    bia
    -0.75
    igel
    -0.75
    xual
    -0.75
    ellen
    -0.74
    POSITIVE LOGITS
     bottled
    1.22
     packaged
    0.83
     peanuts
    0.78
     distilled
    0.77
     beverages
    0.74
     liquor
    0.74
     popcorn
    0.74
     beverage
    0.72
    ãĤ¹ãĥĪ
    0.71
     wastewater
    0.70
    Activations Density 0.015%

    No Known Activations