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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. 4-RES-JB
    6. 8109
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    Explanations

    phrases related to specific individuals or entities, possibly related to sports or business

    oai_token-act-pair · gpt-3.5-turbo

    words related to various forms of "doing" or "performing."

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

    No Comments

    Negative Logits
    Neg
    -0.76
     Leilan
    -0.75
    ublic
    -0.72
    reon
    -0.69
    hemat
    -0.69
    ________________________________________________________________
    -0.67
    ensable
    -0.67
    Weather
    -0.66
    Altern
    -0.66
    WD
    -0.64
    POSITIVE LOGITS
    ning
    1.00
    HAM
    0.95
    ham
    0.84
    stocks
    0.81
    brook
    0.79
    bach
    0.78
    ding
    0.77
    theless
    0.77
    ned
    0.76
    alties
    0.75
    Activations Density 0.013%

    No Known Activations