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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

    the word "radar" with varying degrees of emphasis

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "radar" in various 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
    anza
    -0.81
    bern
    -0.80
    aples
    -0.76
    Latin
    -0.72
    atern
    -0.71
    Kind
    -0.70
    size
    -0.68
    È
    -0.68
    Demon
    -0.67
    adra
    -0.67
    POSITIVE LOGITS
     radar
    1.23
     Radar
    0.94
    ionics
    0.92
     wip
    0.92
    sonian
    0.89
     detectors
    0.85
     absor
    0.83
     antennas
    0.83
     detector
    0.80
     antenna
    0.76
    Activations Density 0.005%

    No Known Activations