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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 1-RES-JB
    6. 19705
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    Explanations

    mentions of locations or areas characterized by high levels of activity or conflict, often associated with negative events

    oai_token-act-pair · gpt-3.5-turbo

    references to "hots" or "hotspots" in various contexts

    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
    ude
    -0.71
    nered
    -0.69
    MT
    -0.68
    aughs
    -0.68
    ŃĶ
    -0.68
    ressive
    -0.63
    yss
    -0.62
     Suff
    -0.62
    ogy
    -0.60
    UTION
    -0.58
    POSITIVE LOGITS
    pots
    1.45
     hots
    1.44
    pot
    1.23
     Hots
    1.11
    hots
    0.97
    bucks
    0.83
    atile
    0.81
    combe
    0.79
    pur
    0.78
    beans
    0.76
    Activations Density 0.005%

    No Known Activations