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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. 3-RES-JB
    6. 2561
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    INDEX
    Explanations

    mentions of specific terms related to the company or brand "Clear Channel" or specific locations such as "Concordia"

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "Clear" and related terms indicating clarity or clearance

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ITAL
    -0.87
    FAULT
    -0.78
    LAB
    -0.74
    Bey
    -0.73
    tackle
    -0.72
    SN
    -0.71
    externalActionCode
    -0.69
    minecraft
    -0.69
    seless
    -0.67
    hed
    -0.67
    POSITIVE LOGITS
    ance
    1.01
     Clear
    0.97
     Seal
    0.87
    Clear
    0.81
    ances
    0.79
     Flags
    0.78
    opsis
    0.77
    Flag
    0.76
     Triangle
    0.76
     Conce
    0.75
    Activations Density 0.021%

    No Known Activations