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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. 7551
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    Explanations

    phrases indicating that attention should be focused or maintained on something specific

    oai_token-act-pair · gpt-3.5-turbo

    expressions related to vigilance or attention

    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
    ivari
    -0.79
    channelAvailability
    -0.77
    minus
    -0.75
    theless
    -0.71
     congr
    -0.68
     Burr
    -0.66
     Bundes
    -0.64
    tons
    -0.63
     Vide
    -0.62
     Violent
    -0.62
    POSITIVE LOGITS
     eye
    0.91
     sockets
    0.86
    light
    0.84
    obl
    0.80
    ight
    0.78
     nose
    0.77
    eyes
    0.76
     socket
    0.75
     Eye
    0.73
    beam
    0.73
    Activations Density 0.015%

    No Known Activations