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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. 7-RES-JB
    6. 5960
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    Explanations

    words related to investigation or enhancement

    oai_token-act-pair · gpt-3.5-turbo

    words related to intense emotional states or experiences

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Kush
    -0.67
     aisle
    -0.64
     uneven
    -0.63
    liners
    -0.60
     Cinema
    -0.60
     driveway
    -0.58
     runway
    -0.58
     spotting
    -0.58
     air
    -0.58
     Circus
    -0.56
    POSITIVE LOGITS
    ment
    0.90
    ¶æ
    0.88
    orial
    0.81
    vous
    0.80
    ments
    0.78
    enced
    0.78
    uel
    0.78
    orate
    0.77
    ement
    0.77
    abil
    0.77
    Activations Density 0.191%

    No Known Activations