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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 11108
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    Explanations

    phrases indicating relevance or importance

    oai_token-act-pair · gpt-3.5-turbo

    phrases that emphasize relevance or significance in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    esta
    -0.63
    itialized
    -0.63
    iple
    -0.60
     Observer
    -0.59
     Conversation
    -0.57
    obar
    -0.56
    Sund
    -0.56
     Barron
    -0.56
     Tray
    -0.55
    anos
    -0.55
    POSITIVE LOGITS
    .[
    0.99
    .
    0.91
    ãĢĤ
    0.88
    .*
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    .</
    0.84
    !.
    0.84
    .''.
    0.79
    .ãĢį
    0.77
     ;)
    0.77
    Activations Density 0.442%

    No Known Activations