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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. 1-RES-JB
    11. 3097
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    Explanations

    statistics related to basketball games, specifically focusing on rebounds

    oai_token-act-pair · gpt-3.5-turbo

    mention of basketball rebounds and turnovers

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    cho
    -0.69
     chau
    -0.67
     Anglo
    -0.66
     Chau
    -0.66
     European
    -0.64
    non
    -0.63
    Lower
    -0.60
    cas
    -0.60
    Premium
    -0.59
    Metro
    -0.59
    POSITIVE LOGITS
     rebounds
    1.29
    oppable
    0.86
    hement
    0.84
    poons
    0.80
    pread
    0.79
    halla
    0.79
    interstitial
    0.78
    heet
    0.78
    pointers
    0.78
     rebound
    0.75
    Activations Density 0.011%

    No Known Activations