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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. 6-RES-JB
    11. 4146
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    Explanations

    wh- words, possibly focusing on conjunctions or pronouns like "who" or "what"

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the substring "wh" in words

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    PORT
    -0.95
    phrine
    -0.81
    HAEL
    -0.78
    ãĥ´ãĤ¡
    -0.76
    Reloaded
    -0.76
    senal
    -0.75
    BuyableInstoreAndOnline
    -0.72
    ITAL
    -0.71
     Sunshine
    -0.70
    hyde
    -0.70
    POSITIVE LOGITS
    omever
    1.20
    inging
    1.08
    ipper
    1.06
    ipp
    1.05
    irling
    1.05
    idd
    1.01
    irlf
    0.99
    ipple
    0.97
    ither
    0.96
    ippers
    0.93
    Activations Density 0.010%

    No Known Activations