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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 6-RES-JB
    11. 15298
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    Explanations

    words related to unhealthy, low-quality, or speculative items like 'junk food' or 'junk science'

    oai_token-act-pair · gpt-3.5-turbo

    references to junk food

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Æ
    -0.79
    oral
    -0.74
    cing
    -0.71
    ignty
    -0.69
    theless
    -0.69
    soType
    -0.65
    uncture
    -0.65
    IRO
    -0.65
    mberg
    -0.64
     Lauder
    -0.64
    POSITIVE LOGITS
     junk
    0.99
     heap
    0.93
     drawer
    0.89
    ies
    0.81
    busters
    0.81
    etsu
    0.80
     pile
    0.79
    ãģı
    0.79
    town
    0.78
     hoard
    0.77
    Activations Density 0.024%

    No Known Activations