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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. 16369
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    Explanations

    words related to estimates, estimations, and imprecise quantifications

    oai_token-act-pair · gpt-3.5-turbo

    words related to estimation and quantification

    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
    spr
    -0.77
    Bloom
    -0.71
     daring
    -0.68
     refreshing
    -0.63
     appealed
    -0.62
     sidel
    -0.62
    shall
    -0.62
    inis
    -0.62
    Else
    -0.61
     Kah
    -0.60
    POSITIVE LOGITS
    imate
    1.40
    imation
    1.00
    oice
    0.94
    imating
    0.89
    imated
    0.88
    imates
    0.87
    ction
    0.82
    andum
    0.81
    itri
    0.80
    lation
    0.77
    Activations Density 0.012%

    No Known Activations