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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. 0-RES-JB
    6. 9166
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    INDEX
    Explanations

    specific terms related to objectives or aspirations

    oai_token-act-pair · gpt-3.5-turbo

    references to "goals" and high-frequency mentions of specific individuals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    oran
    -0.72
     encl
    -0.71
     protections
    -0.69
    hiro
    -0.68
     takedown
    -0.66
    bones
    -0.66
    ropolis
    -0.65
    aeda
    -0.63
    opus
    -0.63
    ubuntu
    -0.63
    POSITIVE LOGITS
     Goal
    2.26
    Goal
    1.77
     Lifetime
    1.75
     Laz
    1.68
    goal
    1.62
    ctive
    1.43
     Mess
    1.25
    cean
    1.09
     Habit
    1.09
    aft
    1.08
    Activations Density 0.049%

    No Known Activations