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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. 2418
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    Explanations

    scores of games

    oai_token-act-pair · gpt-3.5-turbo

    score values from sporting events

    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
    perse
    -0.69
    regor
    -0.67
    onyms
    -0.66
     subp
    -0.64
    isodes
    -0.63
    forms
    -0.62
    ographies
    -0.61
    reads
    -0.61
    chairs
    -0.61
    published
    -0.59
    POSITIVE LOGITS
     halftime
    0.83
     victory
    0.80
     underdog
    0.77
     (.
    0.76
     overall
    0.75
     overtime
    0.71
     rout
    0.71
     margin
    0.66
     win
    0.65
     landslide
    0.65
    Activations Density 0.054%

    No Known Activations