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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. 24375
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    Explanations

    instances where the text prompts the reader or viewer to further educate themselves by learning more about a particular topic or subject

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "learn" and variations of it

    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
    ordered
    -0.77
    abwe
    -0.64
    raviolet
    -0.63
     headed
    -0.61
    ordering
    -0.61
    amination
    -0.60
    lished
    -0.60
    conn
    -0.60
    vati
    -0.58
    ItemTracker
    -0.57
    POSITIVE LOGITS
    Lear
    0.84
     Teach
    0.83
    æ©
    0.82
    learn
    0.81
    llor
    0.78
    æĥ
    0.76
     lessons
    0.75
    edge
    0.73
    ERC
    0.72
     Curve
    0.72
    Activations Density 0.026%

    No Known Activations