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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 4-RES-JB
    6. 3428
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    Explanations

    references to specific numerical statistics in sports such as points and percentages

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "from" 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
    Not in Any Lists

    No Comments

    Negative Logits
    quartered
    -0.74
    heit
    -0.72
    azeera
    -0.72
    ema
    -0.71
    ratulations
    -0.70
    merce
    -0.70
    bush
    -0.69
    idav
    -0.68
    igent
    -0.67
    irm
    -0.65
    POSITIVE LOGITS
     afar
    1.40
     whence
    0.93
     scratch
    0.93
     scrimmage
    0.83
     abroad
    0.82
     inception
    0.78
     inside
    0.78
     anywhere
    0.77
     atop
    0.75
     across
    0.73
    Activations Density 0.150%

    No Known Activations