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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. 7-RES-JB
    11. 11140
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    Explanations

    sporting event results with win-loss records

    oai_token-act-pair · gpt-3.5-turbo

    numerical representations related to sports statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    agna
    -0.71
    arya
    -0.67
    pain
    -0.63
    perse
    -0.62
     Forensic
    -0.62
     Detection
    -0.59
    saf
    -0.59
    don
    -0.59
    objects
    -0.58
    mas
    -0.58
    POSITIVE LOGITS
     overtime
    0.83
     aggregate
    0.78
     overall
    0.71
     FG
    0.70
     underdog
    0.69
     record
    0.69
    ãĤ´ãĥ³
    0.67
     mph
    0.66
     (.
    0.65
    mph
    0.63
    Activations Density 0.039%

    No Known Activations