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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. 470
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    Explanations

    terms related to quantitative analysis or measurements, with a focus on 'quantitative'

    oai_token-act-pair · gpt-3.5-turbo

    terms related to quantitative analysis and extreme ideologies

    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
    rette
    -0.88
     Lann
    -0.83
    heim
    -0.82
    bus
    -0.77
    ille
    -0.76
    raft
    -0.71
    guard
    -0.71
    block
    -0.70
    legate
    -0.70
    cy
    -0.68
    POSITIVE LOGITS
     qualitative
    0.96
    itatively
    0.92
     ultr
    0.84
    ologically
    0.81
    ĨĴ
    0.77
    aturday
    0.73
    anty
    0.73
    asing
    0.73
    yip
    0.73
    sonian
    0.71
    Activations Density 0.023%

    No Known Activations