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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. 6-RES-JB
    11. 4983
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    INDEX
    Explanations

    modal verbs conveying expectation

    oai_token-act-pair · gpt-3.5-turbo

    phrases expressing expectations or anticipations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    soever
    -0.73
    pite
    -0.63
    grounds
    -0.62
     Eps
    -0.62
    ById
    -0.61
     Wasserman
    -0.61
     Esp
    -0.61
    Wan
    -0.60
    hots
    -0.60
     Huma
    -0.60
    POSITIVE LOGITS
     attach
    0.82
     recreate
    0.81
     sell
    0.79
     hear
    0.77
    eat
    0.77
     capitalize
    0.76
     bring
    0.76
     exceed
    0.76
     reap
    0.75
     get
    0.75
    Activations Density 0.186%

    No Known Activations