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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. 6-RES-JB
    11. 7387
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    Explanations

    quantitative words related to measurement, quantity, and magnitude

    oai_token-act-pair · gpt-3.5-turbo

    terms related to measurements and quantities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enegger
    -0.79
    arna
    -0.75
    inka
    -0.72
    sb
    -0.71
    姫
    -0.71
    INA
    -0.69
    ãĤ´ãĥ³
    -0.68
     =================================
    -0.64
    ANA
    -0.64
    çīĪ
    -0.64
    POSITIVE LOGITS
    liest
    0.92
     of
    0.89
    iest
    0.85
     thereof
    0.79
     level
    0.79
     extent
    0.78
     validity
    0.78
     portion
    0.76
     difference
    0.73
     allowable
    0.70
    Activations Density 0.240%

    No Known Activations