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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. 7763
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    INDEX
    Explanations

    mentions of sports teams or events

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of teams and competition

    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
    ©¶æ¥µ
    -0.98
    Library
    -0.70
    ¾
    -0.69
    730
    -0.68
    Liter
    -0.68
    537
    -0.67
     Hamb
    -0.65
    Scroll
    -0.64
    apps
    -0.63
    605
    -0.63
    POSITIVE LOGITS
     against
    2.02
    against
    1.90
     Against
    1.67
     versus
    1.52
     vs
    1.51
    Against
    1.46
     Vs
    1.33
    vs
    1.23
     Versus
    1.21
     VS
    1.07
    Activations Density 0.277%

    No Known Activations