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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. 11918
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    INDEX
    Explanations

    phrases indicating setting objectives or goals

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating the intention or purpose of actions

    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
    eries
    -0.65
    ilege
    -0.62
    antha
    -0.61
    ery
    -0.61
     outage
    -0.60
    atching
    -0.60
    avorable
    -0.60
    essee
    -0.59
    interstitial
    -0.59
    leness
    -0.59
    POSITIVE LOGITS
     anew
    0.87
    fitted
    0.85
    posts
    0.73
    gow
    0.68
    llor
    0.65
    tracks
    0.64
    AAF
    0.64
    Goal
    0.64
    ¯¯¯¯¯¯¯¯
    0.64
    ngth
    0.63
    Activations Density 0.047%

    No Known Activations