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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. 2-RES-JB
    6. 1255
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    Explanations

    the name "Waters" with different levels of emphasis, likely indicating relevance or importance in the context of the text

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the name 'Waters'

    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
    oard
    -0.70
    ERAL
    -0.69
    bable
    -0.68
    erous
    -0.66
     conviction
    -0.62
    obs
    -0.62
    OTS
    -0.62
     consideration
    -0.62
     conceal
    -0.61
     centralized
    -0.61
    POSITIVE LOGITS
     Waters
    1.19
    waters
    0.96
    melon
    0.94
    bats
    0.92
    hed
    0.85
    hip
    0.85
    combe
    0.83
    boro
    0.82
    pin
    0.82
    geist
    0.82
    Activations Density 0.006%

    No Known Activations