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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. 13747
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    Explanations

    moments of significant information or actions

    oai_token-act-pair · gpt-3.5-turbo

    sentences that describe the nature or difficulty of tasks and experiences

    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
    dylib
    -0.76
    stood
    -0.67
     throats
    -0.67
    luaj
    -0.64
     withdrew
    -0.63
     sockets
    -0.61
     Rohing
    -0.60
    iat
    -0.60
    iol
    -0.59
     Peb
    -0.59
    POSITIVE LOGITS
     tricky
    1.03
     akin
    0.99
     fraught
    0.98
     easier
    0.97
     risky
    0.96
     stressful
    0.95
     daunting
    0.94
     exhausting
    0.94
     cumbersome
    0.92
     easy
    0.90
    Activations Density 0.278%

    No Known Activations