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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. 3663
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    Explanations

    statements related to projected or expected outcomes in a negative context

    oai_token-act-pair · gpt-3.5-turbo

    numerical data or statistics related to various topics

    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
    boro
    -0.73
    heit
    -0.64
    utics
    -0.62
    utical
    -0.61
    ales
    -0.57
     contempl
    -0.56
    apes
    -0.55
     Breed
    -0.55
    utic
    -0.55
    isma
    -0.55
    POSITIVE LOGITS
    Specifically
    0.93
    Writing
    0.78
    ccording
    0.77
    lished
    0.76
    PHOTOS
    0.75
    Ironically
    0.72
    However
    0.71
    Eh
    0.71
    Think
    0.70
    ³³³³
    0.69
    Activations Density 0.572%

    No Known Activations