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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. 3-RES-JB
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    Explanations

    mentions of strong winds and weather phenomena

    oai_token-act-pair · gpt-3.5-turbo

    terms related to strong winds and their effects

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    tein
    -0.82
    bour
    -0.68
    atern
    -0.66
    Ô
    -0.64
    arenthood
    -0.64
    Pie
    -0.62
     Flavoring
    -0.62
     Bour
    -0.61
    ared
    -0.61
    rius
    -0.61
    POSITIVE LOGITS
     winds
    1.17
     gust
    1.06
    storms
    1.04
     currents
    0.95
     Winds
    0.93
     wind
    0.87
     chill
    0.85
     turbines
    0.85
     blowing
    0.85
     breeze
    0.84
    Activations Density 0.015%

    No Known Activations