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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. 2490
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    Explanations

    references to particulate matter (PM) concentrations

    oai_token-act-pair · gpt-3.5-turbo
    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
    combe
    -0.82
    come
    -0.80
    kers
    -0.70
    seeing
    -0.70
    bern
    -0.67
    ttes
    -0.67
    inese
    -0.64
    ker
    -0.64
    keye
    -0.63
    tyard
    -0.62
    POSITIVE LOGITS
    PD
    0.96
    ORTS
    0.95
    essage
    0.87
    Cs
    0.86
    ULE
    0.83
    ION
    0.82
    VP
    0.81
    OND
    0.81
    OD
    0.80
    ETS
    0.80
    Activations Density 0.047%

    No Known Activations