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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 22832
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    Explanations

    mentions of the word "Mill" followed by a numerical value

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the word "Mill" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     compr
    -0.77
     manifest
    -0.72
     screened
    -0.66
     anat
    -0.63
     effected
    -0.62
     arous
    -0.62
     reass
    -0.62
     compelling
    -0.62
     coordinated
    -0.62
     ende
    -0.61
    POSITIVE LOGITS
    enium
    1.62
    isec
    1.26
    imet
    1.21
    imeter
    1.12
    icent
    1.12
    iard
    1.08
    igans
    1.06
    imeters
    1.06
    enn
    1.04
    inery
    1.04
    Activations Density 0.011%

    No Known Activations