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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. 9-RES-JB
    11. 13983
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    Explanations

    phrases related to urgency or importance with some focusing on news or event highlights

    oai_token-act-pair · gpt-3.5-turbo

    the phrase "Must watch" and its variations, particularly in context of videos or content that is deemed important or significant

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    urious
    -0.80
    sth
    -0.78
    icum
    -0.77
    orthy
    -0.75
    ãĥ¼ãĥĨãĤ£
    -0.72
    baugh
    -0.70
    pot
    -0.68
    dump
    -0.68
    raq
    -0.67
    ston
    -0.67
    POSITIVE LOGITS
     wors
    0.52
     worsened
    0.52
     stare
    0.52
     adherence
    0.51
     motto
    0.51
     reputation
    0.50
     attRot
    0.50
     recomm
    0.49
     Governments
    0.49
     replaced
    0.49
    Activations Density 0.480%

    No Known Activations