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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. 6-RES-JB
    11. 572
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    Explanations

    phrases indicating some form of quantification, typically related to an unspecified quantity or degree

    oai_token-act-pair · gpt-3.5-turbo

    references to quantitative assessments or implications

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     craw
    -0.66
     itch
    -0.64
     bread
    -0.62
     bond
    -0.61
    lite
    -0.61
     sled
    -0.61
    away
    -0.58
     broom
    -0.58
     resonance
    -0.57
    inelli
    -0.57
    POSITIVE LOGITS
    awei
    0.95
    entially
    0.92
    encies
    0.90
    ¤
    0.85
    ngth
    0.84
    externalActionCode
    0.77
    illac
    0.76
    ensions
    0.75
    uates
    0.73
     Approximately
    0.73
    Activations Density 0.031%

    No Known Activations