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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. 15124
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    Explanations

    numbers in the format of thousands (e.g., 000) with high activation levels

    oai_token-act-pair · gpt-3.5-turbo

    numeric values expressed in thousands

    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
    swick
    -0.78
    warts
    -0.78
    illard
    -0.73
    krit
    -0.73
    riot
    -0.71
    icka
    -0.69
    vironment
    -0.69
    agall
    -0.67
     weakness
    -0.66
    vation
    -0.66
    POSITIVE LOGITS
     000
    0.81
    Mbps
    0.81
     è£ıè¦ļéĨĴ
    0.75
    Hz
    0.74
    ãĥ©ãĥ³
    0.72
     Hz
    0.70
    mAh
    0.70
    HT
    0.70
    364
    0.70
    000
    0.69
    Activations Density 0.061%

    No Known Activations