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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. 4-RES-JB
    11. 4446
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    Explanations

    words related to focal points or central aspects

    oai_token-act-pair · gpt-3.5-turbo

    key terms associated with central themes or focal points in various contexts

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

    No Comments

    Negative Logits
    eem
    -0.76
    odcast
    -0.73
    cham
    -0.72
    resso
    -0.71
    atson
    -0.70
    atto
    -0.65
     assimil
    -0.65
     Byrne
    -0.65
    umble
    -0.65
     Merrill
    -0.64
    POSITIVE LOGITS
     focal
    1.15
    istics
    0.84
     ray
    0.77
    rative
    0.75
     attraction
    0.75
     flare
    0.73
    imation
    0.72
     artery
    0.72
     flares
    0.72
    rator
    0.71
    Activations Density 0.014%

    No Known Activations