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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
    11. 13251
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    Explanations

    keywords related to liners, such as ship liners or other types of liners

    oai_token-act-pair · gpt-3.5-turbo

    references to specific types of ships, particularly liners

    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
    achu
    -0.88
     Seym
    -0.78
    ortion
    -0.75
    orsi
    -0.74
    76561
    -0.73
    ifully
    -0.71
    rity
    -0.68
    nown
    -0.67
    icably
    -0.67
    ategory
    -0.67
    POSITIVE LOGITS
    ptin
    0.88
    liner
    0.80
    CLA
    0.76
     Sans
    0.71
    utenant
    0.69
    cest
    0.69
    jad
    0.67
    estyle
    0.67
     Ital
    0.66
    pper
    0.66
    Activations Density 0.023%

    No Known Activations