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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
    11. 11909
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    Explanations

    phrases referring to quantity, specifically the word "many" with varying levels of intensity

    oai_token-act-pair · gpt-3.5-turbo

    the frequency of the word "many" in 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
    ICO
    -0.84
    POSE
    -0.82
    IER
    -0.77
    Market
    -0.71
    onential
    -0.67
    ision
    -0.66
    KO
    -0.66
     Uri
    -0.66
    ERSON
    -0.65
    ema
    -0.64
    POSITIVE LOGITS
     facets
    0.94
     complexities
    0.85
     possibilities
    0.82
     ways
    0.77
     nuances
    0.76
     contradictions
    0.75
    ness
    0.74
     iterations
    0.74
    liest
    0.73
     creations
    0.72
    Activations Density 0.082%

    No Known Activations