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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 12495
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    Explanations

    statistics related to sports performance

    oai_token-act-pair · gpt-3.5-turbo

    numerical statistics related to sports performance

    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
    Asia
    -0.78
     Canaver
    -0.76
     nort
    -0.75
    Lago
    -0.73
    ©¶æ
    -0.72
     Caucas
    -0.71
    osate
    -0.68
    cale
    -0.67
    Term
    -0.67
     Applicant
    -0.67
    POSITIVE LOGITS
     assists
    1.36
     rebounds
    1.31
     steals
    1.09
     interceptions
    1.08
     touchdowns
    0.95
     turnovers
    0.93
     assist
    0.93
     interception
    0.89
     rebound
    0.87
     receptions
    0.84
    Activations Density 0.086%

    No Known Activations