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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. 8-RES-JB
    11. 8030
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    Explanations

    phrases related to investigating and identifying causes or reasons for events or conditions

    oai_token-act-pair · gpt-3.5-turbo

    references to causes of incidents or issues

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    rim
    -0.81
    rons
    -0.79
    owship
    -0.76
    buff
    -0.74
    NRS
    -0.73
    rob
    -0.70
    mun
    -0.67
    isse
    -0.65
    Pixel
    -0.65
    reens
    -0.64
    POSITIVE LOGITS
     WHY
    0.94
    why
    0.89
     attribut
    0.88
     motives
    0.88
     thereof
    0.87
     why
    0.87
     behind
    0.83
     attributed
    0.80
     motive
    0.79
     underlying
    0.75
    Activations Density 0.141%

    No Known Activations