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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. 5294
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    Explanations

    words related to outcomes and results

    oai_token-act-pair · gpt-3.5-turbo

    references to outcomes and their implications

    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
    andise
    -0.78
    mans
    -0.73
    ondo
    -0.72
    yi
    -0.72
    asus
    -0.71
    uni
    -0.70
    agine
    -0.69
    ular
    -0.68
    ordes
    -0.66
    udi
    -0.66
    POSITIVE LOGITS
     outcome
    1.01
     outcomes
    0.94
    bringer
    0.87
     thereof
    0.85
     probabilities
    0.78
    uates
    0.77
     expectancy
    0.76
    aries
    0.70
     Pact
    0.69
     vict
    0.69
    Activations Density 0.036%

    No Known Activations