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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. 6154
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    Explanations

    mentions of winning and losing outcomes

    oai_token-act-pair · gpt-3.5-turbo

    terms related to winning and success in competitive contexts

    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
     incorpor
    -0.69
     intestine
    -0.64
     bowel
    -0.64
     Fires
    -0.59
     forks
    -0.59
     copying
    -0.57
     cens
    -0.57
     bom
    -0.57
     rendition
    -0.56
     Traffic
    -0.56
    POSITIVE LOGITS
    nings
    1.54
    throp
    1.14
    stre
    1.09
    now
    1.06
     streak
    1.03
    less
    0.94
    ery
    0.94
    cing
    0.93
    eries
    0.91
    ners
    0.90
    Activations Density 0.034%

    No Known Activations