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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. 1613
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    Explanations

    specific time references within a sports context

    oai_token-act-pair · gpt-3.5-turbo

    time-related references and scoring events in sports contexts

    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
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    No Comments

    Negative Logits
    azeera
    -0.78
    Sov
    -0.73
    oras
    -0.71
    itarian
    -0.69
     curric
    -0.69
    chwitz
    -0.69
    catentry
    -0.65
    sonian
    -0.65
     yearly
    -0.64
     associations
    -0.63
    POSITIVE LOGITS
    ftime
    0.91
     scoreboard
    0.87
     scorer
    0.84
     opener
    0.84
     stopp
    0.81
     halftime
    0.80
     scoring
    0.78
     scored
    0.74
     shootout
    0.74
     unbeaten
    0.71
    Activations Density 0.117%

    No Known Activations