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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. 9-RES-JB
    6. 650
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    Explanations

    words related to meeting a specific standard or requirement

    oai_token-act-pair · gpt-3.5-turbo

    terms related to qualification or eligibility criteria

    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
     Gardens
    -0.77
     Lans
    -0.71
     Torn
    -0.71
     Spice
    -0.69
    eland
    -0.66
     wrinkles
    -0.63
     drip
    -0.63
    orah
    -0.62
     rook
    -0.61
    aging
    -0.61
    POSITIVE LOGITS
    ifies
    1.05
    ifications
    1.05
    ifiers
    1.01
    ifying
    0.99
    itatively
    0.95
    ifier
    0.86
    IFIED
    0.85
    animous
    0.84
    iotics
    0.84
     qualifications
    0.81
    Activations Density 0.027%

    No Known Activations