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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. 7-RES-JB
    6. 15095
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    Explanations

    units of measurement and quantities

    oai_token-act-pair · gpt-3.5-turbo

    units of measurement and quantities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    odon
    -0.70
     Stra
    -0.69
     resent
    -0.69
    amate
    -0.67
     disple
    -0.63
    olia
    -0.60
    zos
    -0.59
    lah
    -0.58
    MJ
    -0.58
     hawk
    -0.58
    POSITIVE LOGITS
     apiece
    0.92
     increments
    0.85
    ãĥİ
    0.81
     Ago
    0.80
     ABV
    0.71
     Radius
    0.70
    bsp
    0.68
     Difficulty
    0.68
    BIT
    0.67
    #$#$
    0.67
    Activations Density 0.197%

    No Known Activations