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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. 9-RES-JB
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    Explanations

    adjectives expressing differing levels of intensity or opinion

    oai_token-act-pair · gpt-3.5-turbo

    adjectives and their intensifiers that describe the quality of experiences or opinions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    xit
    -0.77
    arser
    -0.75
    thood
    -0.72
    iatrics
    -0.65
    hner
    -0.62
    algia
    -0.62
    arer
    -0.62
    usalem
    -0.61
    elines
    -0.60
    ¬¼
    -0.59
    POSITIVE LOGITS
     indeed
    1.23
     (~
    0.90
     (>
    0.88
     considering
    0.82
     nowadays
    0.78
     sounding
    0.76
     insofar
    0.74
    ––
    0.69
     compared
    0.69
    idious
    0.68
    Activations Density 0.315%

    No Known Activations