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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 7-RES-JB
    6. 2412
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    Explanations

    mentions of containers such as jars or cans, especially those with specific contents or purposes

    oai_token-act-pair · gpt-3.5-turbo

    references to jars and cans

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     militias
    -0.70
    voice
    -0.69
     Fighters
    -0.68
     imperson
    -0.68
     streng
    -0.66
    nom
    -0.62
     commute
    -0.62
     procedural
    -0.62
     defe
    -0.61
     antagonist
    -0.61
    POSITIVE LOGITS
     containing
    1.16
     bottles
    1.03
     jars
    0.99
     contents
    0.89
     labeled
    0.88
     cans
    0.88
     jar
    0.88
    poons
    0.88
    poon
    0.88
     lid
    0.86
    Activations Density 0.202%

    No Known Activations