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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 3-RES-JB
    6. 19339
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    Explanations

    instances where something or someone is performing better than expected or outperforming others in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    terms that indicate superior performance or achievements

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Geneva
    -0.78
    Maps
    -0.71
     Franch
    -0.69
    Ale
    -0.66
    RAW
    -0.64
    oslov
    -0.63
    SF
    -0.62
     Refuge
    -0.62
    Gamer
    -0.62
     Anat
    -0.61
    POSITIVE LOGITS
    ceed
    1.03
     outper
    0.94
    performing
    0.93
    atility
    0.85
    rolet
    0.83
    imates
    0.81
    mented
    0.80
    formed
    0.77
    onent
    0.76
    inished
    0.76
    Activations Density 0.004%

    No Known Activations