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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. 2-RES-JB
    6. 19097
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    Explanations

    terms related to marking or identification, possibly involving evaluation or categorization

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "marks" which denotes significance or highlights in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ILLE
    -0.68
     Garner
    -0.68
    æ©Ł
    -0.68
    ADS
    -0.68
    erest
    -0.65
    ECD
    -0.65
     disproportionate
    -0.64
     Fernand
    -0.61
    onz
    -0.59
     Huang
    -0.59
    POSITIVE LOGITS
    manship
    1.46
    marks
    1.07
     marks
    1.00
    mas
    0.94
    mark
    0.89
    terday
    0.89
    emark
    0.89
    hift
    0.87
    pring
    0.84
    pelled
    0.84
    Activations Density 0.007%

    No Known Activations