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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. 7-RES-JB
    11. 3628
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    Explanations

    quantifiable measurements or resources such as volume, data, or amount in a unit

    oai_token-act-pair · gpt-3.5-turbo

    references to quantities of natural resources, substances, or materials

    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
    ":"/
    -0.63
     Jury
    -0.62
     Terror
    -0.62
     tribes
    -0.61
     Kling
    -0.60
     Athe
    -0.60
     BUS
    -0.60
     Scenes
    -0.59
    ãĤ´ãĥ³
    -0.59
    trak
    -0.59
    POSITIVE LOGITS
     apiece
    1.19
     per
    0.88
     (~
    0.82
     deposited
    0.80
     allocated
    0.77
     crammed
    0.75
     compared
    0.73
     annually
    0.72
    votes
    0.68
     depending
    0.68
    Activations Density 0.268%

    No Known Activations