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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    Explanations

    mentions of various types of vegetables

    oai_token-act-pair · gpt-3.5-turbo

    mentions of vegetables

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    raints
    -0.81
    raped
    -0.79
    oning
    -0.75
    ORN
    -0.73
    ammy
    -0.70
    rams
    -0.67
     Standing
    -0.66
    inen
    -0.64
    ederal
    -0.64
    issued
    -0.64
    POSITIVE LOGITS
     vegetables
    1.19
     vegetable
    1.04
     cabbage
    0.98
     Veget
    0.94
     veggies
    0.90
     beet
    0.86
    cake
    0.83
     eater
    0.83
     cris
    0.82
     foods
    0.82
    Activations Density 0.011%

    No Known Activations