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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. 3-RES-JB
    11. 3054
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    INDEX
    Explanations

    references to intense interests or fixations, often with a negative connotation

    oai_token-act-pair · gpt-3.5-turbo

    mentions of obsession or a strong fixation on various topics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    stood
    -0.91
    annis
    -0.70
    ĻĤ
    -0.67
    sung
    -0.67
    ģ«
    -0.66
    Reviewed
    -0.65
    NAS
    -0.64
     angels
    -0.62
    authent
    -0.62
    reens
    -0.61
    POSITIVE LOGITS
    ishly
    0.85
     fascination
    0.81
     fixation
    0.81
    ively
    0.80
    uously
    0.79
     obsession
    0.76
    iously
    0.73
     persisted
    0.71
     hobby
    0.68
     fascinated
    0.67
    Activations Density 0.016%

    No Known Activations