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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. 10-RES-JB
    11. 10363
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    Explanations

    sports-related statistics and commentaries

    oai_token-act-pair · gpt-3.5-turbo

    performance statistics related to sports or competitive activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enegger
    -0.90
    izoph
    -0.65
     beh
    -0.62
    respond
    -0.60
    indust
    -0.60
    schild
    -0.60
    Prin
    -0.60
    ocol
    -0.60
    opath
    -0.59
    bara
    -0.59
    POSITIVE LOGITS
     QB
    1.12
     quarterback
    1.12
     quarterbacks
    1.07
     Pacers
    1.07
     TCU
    1.07
     linebackers
    1.06
     Packers
    1.05
     Bengals
    1.05
     defenseman
    1.04
     Playoff
    1.04
    Activations Density 0.941%

    No Known Activations