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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. 1-RES-JB
    11. 9098
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    Explanations

    phrases related to film production settings, such as "sets of accumulated data" and "wonderful period sets."

    oai_token-act-pair · gpt-3.5-turbo

    references to "sets" associated with various contexts or topics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    gary
    -0.70
    Cath
    -0.66
     Biblical
    -0.66
    Mah
    -0.64
    Death
    -0.64
     Souls
    -0.63
    Jay
    -0.62
    gee
    -0.62
    æѦ
    -0.61
     Commonwealth
    -0.61
    POSITIVE LOGITS
     showc
    1.23
    etting
    0.85
     Sets
    0.81
    ets
    0.79
     sets
    0.79
     forth
    0.79
    tering
    0.78
    ters
    0.78
    itia
    0.77
    omething
    0.77
    Activations Density 0.009%

    No Known Activations