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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. 7638
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    Explanations

    phrases related to monitoring or keeping watch over something specific

    oai_token-act-pair · gpt-3.5-turbo

    phrases about monitoring or observing something

    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
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    Negative Logits
    venge
    -0.74
     Pwr
    -0.73
     Loft
    -0.71
    MAL
    -0.67
    HAHAHAHA
    -0.67
     GI
    -0.64
     DRAG
    -0.61
     Infinite
    -0.59
    AFTA
    -0.58
    illard
    -0.58
    POSITIVE LOGITS
    emark
    0.80
    daq
    0.74
    monitor
    0.73
    lishing
    0.72
    ocobo
    0.71
    atches
    0.69
    yk
    0.68
    aeper
    0.67
    riks
    0.66
    gency
    0.65
    Activations Density 0.049%

    No Known Activations