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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. 5289
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    Explanations

    quantitative descriptors of the degree or amount of something

    oai_token-act-pair · gpt-3.5-turbo

    terms indicating low or minimal impact or significance

    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
    ortment
    -0.83
    ools
    -0.69
    arlane
    -0.66
    mosp
    -0.65
    akeru
    -0.64
    irit
    -0.62
    hemy
    -0.62
     bow
    -0.60
    ogie
    -0.59
    uddin
    -0.58
    POSITIVE LOGITS
     enough
    0.95
     compared
    0.92
    aneously
    0.86
    izable
    0.79
    .
    0.75
    ened
    0.74
    .>>
    0.73
    enough
    0.73
    ;
    0.70
    ised
    0.70
    Activations Density 0.296%

    No Known Activations