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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
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    INDEX
    Explanations

    words related to strong interest or fixation on a specific subject

    oai_token-act-pair · gpt-3.5-turbo

    the concept of obsession and its various contexts

    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
    stood
    -0.80
     Kavanaugh
    -0.68
    reens
    -0.68
    arnaev
    -0.68
    \\\\\\\\
    -0.67
    adr
    -0.66
    ģ«
    -0.66
    Medic
    -0.62
    OUT
    -0.62
    received
    -0.61
    POSITIVE LOGITS
     fascination
    0.84
    ishly
    0.83
     fascinated
    0.77
     obs
    0.75
    ilyn
    0.74
     obsession
    0.73
    ulously
    0.73
    iously
    0.72
     fixation
    0.72
     obsess
    0.70
    Activations Density 0.042%

    No Known Activations