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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. 1-RES-JB
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    Explanations

    references to yards gained or lost in various contexts, particularly in sports

    oai_token-act-pair · gpt-3.5-turbo

    references to yards gained in sporting contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orescent
    -0.77
    ebus
    -0.70
    emia
    -0.70
    nce
    -0.69
    mble
    -0.68
    oxide
    -0.67
    uria
    -0.64
    isen
    -0.64
     inval
    -0.64
    ipper
    -0.63
    POSITIVE LOGITS
     yards
    1.11
     yard
    0.85
    yards
    0.82
     TDs
    0.80
     metres
    0.75
    yard
    0.74
    ometers
    0.72
     touchdowns
    0.70
     earthqu
    0.68
     touchdown
    0.68
    Activations Density 0.008%

    No Known Activations