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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. 8-RES-JB
    11. 12300
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    Explanations

    instances of people being observed or spotted doing various activities

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "seen" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    angan
    -0.73
    idity
    -0.72
    EStreamFrame
    -0.70
    yright
    -0.65
     understatement
    -0.63
    mental
    -0.62
    ulum
    -0.62
    aceutical
    -0.62
     sclerosis
    -0.60
    endiary
    -0.59
    POSITIVE LOGITS
    seeing
    0.79
    wcsstore
    0.77
    agascar
    0.75
    IRT
    0.74
    dust
    0.74
    qt
    0.69
    á½
    0.69
     fit
    0.69
    Model
    0.69
    ById
    0.68
    Activations Density 0.053%

    No Known Activations