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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. 5908
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    Explanations

    details about appearances in various sports games

    oai_token-act-pair · gpt-3.5-turbo

    the statistics and achievements of athletes 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
    Not in Any Lists

    No Comments

    Negative Logits
     sensibilities
    -0.65
    luaj
    -0.64
     currents
    -0.63
     promises
    -0.62
     probabilities
    -0.61
    $$$$
    -0.61
    rity
    -0.61
     tastes
    -0.59
     Creat
    -0.59
     priorities
    -0.57
    POSITIVE LOGITS
     innings
    0.76
     scrimmage
    0.75
    inous
    0.74
    ibaba
    0.73
     intercepted
    0.72
     entirety
    0.72
    irteen
    0.72
     pinch
    0.70
     Bundesliga
    0.70
     stint
    0.68
    Activations Density 0.170%

    No Known Activations