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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. 4-RES-JB
    11. 16701
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    Explanations

    phrases related to data processing

    oai_token-act-pair · gpt-3.5-turbo

    references to processing in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    liest
    -0.79
    fall
    -0.72
    gets
    -0.71
    ortium
    -0.69
    gged
    -0.67
    lihood
    -0.66
    show
    -0.65
    sky
    -0.64
    lar
    -0.63
     oblig
    -0.63
    POSITIVE LOGITS
     Processing
    1.06
     processing
    1.01
    processing
    0.82
    utical
    0.81
    process
    0.80
     processors
    0.80
    avascript
    0.79
    IME
    0.79
    folios
    0.79
     ãĤµãĥ¼ãĥĨãĤ£ãĥ¯ãĥ³
    0.78
    Activations Density 0.021%

    No Known Activations