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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 2-RES-JB
    6. 4637
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    Explanations

    words related to the field of econometrics, especially terms related to Bayeisan econometrics

    oai_token-act-pair · gpt-3.5-turbo

    terms related to 'metrics' and 'econometrics'

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    selection
    -0.77
    cloth
    -0.70
    case
    -0.67
    PLA
    -0.63
     hearing
    -0.61
     [+
    -0.61
     situ
    -0.59
    context
    -0.58
    SPONSORED
    -0.58
     Supplemental
    -0.58
    POSITIVE LOGITS
    imet
    1.29
    omet
    1.07
    rics
    1.05
    allic
    1.04
    ool
    0.89
    rix
    0.86
    rium
    0.86
    abolic
    0.85
    rates
    0.84
    rial
    0.84
    Activations Density 0.006%

    No Known Activations