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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. 5-RES-JB
    6. 10329
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    Explanations

    keywords related to pinpointing, spotting, recognizing, and identifying specific information or features

    oai_token-act-pair · gpt-3.5-turbo

    terms related to detection and identification processes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    udeb
    -0.73
    cloth
    -0.71
    Sov
    -0.71
    adra
    -0.69
    ylum
    -0.69
    undy
    -0.67
    usp
    -0.66
    rette
    -0.65
    orld
    -0.65
    HOU
    -0.63
    POSITIVE LOGITS
    alys
    0.86
    ibly
    0.82
     detect
    0.81
     Detect
    0.80
     detecting
    0.79
    pell
    0.76
     neural
    0.75
     accurately
    0.75
     accuracy
    0.74
     Accuracy
    0.73
    Activations Density 0.288%

    No Known Activations