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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. 10-RES-JB
    6. 3606
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    INDEX
    Explanations

    the word "many" with a high activation level

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "many" 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
    agame
    -0.77
    UAL
    -0.74
    icism
    -0.70
    ESE
    -0.69
    atown
    -0.68
    anut
    -0.67
    aban
    -0.65
    abus
    -0.64
    OPE
    -0.64
    heed
    -0.63
    POSITIVE LOGITS
     facets
    1.21
     thousands
    1.07
     different
    1.06
     times
    1.05
     kinds
    1.02
     aspects
    1.01
     occasions
    0.99
     years
    0.94
     iterations
    0.93
     thousand
    0.93
    Activations Density 0.085%

    No Known Activations