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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. 9-RES-JB
    11. 2868
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    Explanations

    descriptions of scenes or scenarios involving people gathered in a specific location

    oai_token-act-pair · gpt-3.5-turbo

    situations involving gatherings or groups of people

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    osate
    -0.87
    inventoryQuantity
    -0.84
    uably
    -0.79
     Investor
    -0.69
     Comprehensive
    -0.68
     Gain
    -0.67
    essee
    -0.66
    ornia
    -0.66
     predecessor
    -0.66
    ozy
    -0.66
    POSITIVE LOGITS
    selves
    1.05
     themselves
    1.03
     chanting
    1.02
     unison
    0.95
     frantically
    0.92
     shouting
    0.92
     silently
    0.92
     applaud
    0.91
     nervously
    0.91
     spectators
    0.91
    Activations Density 0.504%

    No Known Activations