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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. 5913
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    Explanations

    questions starting with "How do you" or "How do we" followed by certain actions or situations, possibly related to problem-solving or decision-making

    oai_token-act-pair · gpt-3.5-turbo
    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
    requisite
    -0.70
    Runner
    -0.69
    letter
    -0.68
    skirts
    -0.65
    asca
    -0.64
    yip
    -0.62
    teness
    -0.61
    Cra
    -0.61
    requisites
    -0.61
    iki
    -0.60
    POSITIVE LOGITS
     reconcile
    1.24
     cope
    1.04
     reconcil
    1.01
     differentiate
    0.94
     navigate
    0.91
     handle
    0.91
     distinguish
    0.90
     ensure
    0.90
     react
    0.90
     justify
    0.90
    Activations Density 0.107%

    No Known Activations