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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. 16683
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    INDEX
    Explanations

    sport teams or matches, specifically focusing on rankings and results

    oai_token-act-pair · gpt-3.5-turbo

    sports teams and their rankings or standings in competitions

    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
    EVA
    -0.87
    Offline
    -0.75
    inventoryQuantity
    -0.72
    anasia
    -0.72
     condol
    -0.71
    ategory
    -0.68
    afety
    -0.68
    ortment
    -0.68
     workflow
    -0.68
     backstage
    -0.64
    POSITIVE LOGITS
     Tigers
    1.47
     Eagles
    1.43
     Panthers
    1.40
     Cavaliers
    1.40
     Broncos
    1.39
     Falcons
    1.38
     Bulldogs
    1.37
     Blazers
    1.37
     Cardinals
    1.36
     Buccaneers
    1.36
    Activations Density 0.691%

    No Known Activations