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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. 9-RES-JB
    11. 23628
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    Explanations

    webpage interaction prompts, specifically ones related to enabling JavaScript, watching videos, and clicking to view content

    oai_token-act-pair · gpt-3.5-turbo

    terms related to watching or interacting with video content and the associated actions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Factor
    -0.59
    nikov
    -0.53
     lin
    -0.53
     awa
    -0.52
    lihood
    -0.51
    tes
    -0.50
     liner
    -0.50
     caution
    -0.50
    ances
    -0.50
    warm
    -0.49
    POSITIVE LOGITS
    IVE
    0.64
    uren
    0.60
    Widget
    0.55
    yright
    0.54
    ona
    0.54
    Untitled
    0.54
    hent
    0.54
    LLOW
    0.54
    atalie
    0.54
    margin
    0.53
    Activations Density 0.105%

    No Known Activations