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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
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    Explanations

    references to events related to sports preseason

    oai_token-act-pair · gpt-3.5-turbo

    references to preseason sports events

    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
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    Negative Logits
    manship
    -0.93
    vic
    -0.85
    meal
    -0.84
    gin
    -0.83
    meyer
    -0.82
    room
    -0.81
    lessness
    -0.81
    matic
    -0.79
    nce
    -0.77
    gun
    -0.76
    POSITIVE LOGITS
    agher
    0.85
    ascus
    0.83
    ocular
    0.76
    oulos
    0.74
     Plain
    0.68
    halla
    0.68
     futures
    0.66
    ère
    0.66
    atcher
    0.64
    erences
    0.63
    Activations Density 0.144%

    No Known Activations