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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. 10-RES-JB
    11. 6873
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    Explanations

    phrases related to the output or outcome of a process or analysis

    oai_token-act-pair · gpt-3.5-turbo

    references to "results" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    resent
    -0.73
     Passage
    -0.69
    agine
    -0.66
     Roots
    -0.66
    pton
    -0.64
    ategory
    -0.63
    erness
    -0.61
    thur
    -0.60
    conservancy
    -0.60
     barb
    -0.58
    POSITIVE LOGITS
    iveness
    0.95
    aries
    0.92
    ivity
    0.92
    ively
    0.91
     thereof
    0.76
     results
    0.75
     obtained
    0.71
    results
    0.71
    ivism
    0.69
    ions
    0.68
    Activations Density 0.048%

    No Known Activations