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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. 9-RES-JB
    11. 5536
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    INDEX
    Explanations

    words related to consumption or intake of various items, especially focused on the negative impacts

    oai_token-act-pair · gpt-3.5-turbo

    terms related to the concept of consumption and its associated metrics

    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
    Not in Any Lists

    No Comments

    Negative Logits
     Sharif
    -0.70
    iola
    -0.67
    imov
    -0.66
     awarding
    -0.62
    apply
    -0.61
    maxwell
    -0.59
    syn
    -0.58
     handshake
    -0.58
    iasis
    -0.58
     Pon
    -0.56
    POSITIVE LOGITS
     habits
    1.03
     consumption
    0.97
    iture
    0.93
     Consumption
    0.92
    itures
    0.89
     calories
    0.82
     juices
    0.79
     quantities
    0.77
    umes
    0.76
     gallons
    0.75
    Activations Density 0.050%

    No Known Activations