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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. 4-RES-JB
    6. 4941
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    Explanations

    adjectives related to responsiveness

    oai_token-act-pair · gpt-3.5-turbo

    terms related to responsiveness and attentiveness

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

    No Comments

    Negative Logits
    obyl
    -0.98
    redit
    -0.83
     Munich
    -0.82
    rug
    -0.80
    hammer
    -0.79
    ç¥ŀ
    -0.77
     Bav
    -0.77
    our
    -0.73
    ################
    -0.72
    celona
    -0.70
    POSITIVE LOGITS
     responsive
    1.06
     responsiveness
    1.00
    responsive
    0.95
     intellig
    0.83
    ibilities
    0.80
    encies
    0.80
    ibly
    0.76
     agre
    0.71
     Respons
    0.70
     element
    0.70
    Activations Density 0.014%

    No Known Activations