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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. 0-RES-JB
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    INDEX
    Explanations

    mentions of the word "readers."

    oai_token-act-pair · gpt-3.5-turbo

    references to readers or the audience in the context of literature or media

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    tin
    -0.70
    ename
    -0.64
    ides
    -0.63
    wayne
    -0.62
     Bringing
    -0.61
    Ë
    -0.58
    imar
    -0.58
    phe
    -0.58
     ceremonial
    -0.58
    aband
    -0.57
    POSITIVE LOGITS
     readers
    4.00
     reader
    3.02
     Readers
    2.85
     listeners
    2.41
     viewers
    2.19
     Reader
    2.01
     commenters
    1.86
     editors
    1.85
     subscribers
    1.80
     audiences
    1.80
    Activations Density 0.011%

    No Known Activations