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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. 5-RES-JB
    6. 12198
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    Explanations

    mentions of technology terms, specifically related to screen resolution (e.g., 4K) with a particular emphasis on higher resolution (9 or 10K)

    oai_token-act-pair · gpt-3.5-turbo

    instances of the letter "K" followed by various numerical values

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    terday
    -0.66
     mosqu
    -0.63
     Adin
    -0.62
    ional
    -0.59
     rupt
    -0.58
     Jinn
    -0.58
    querque
    -0.58
    phrine
    -0.58
     Dull
    -0.57
    ãĥ¯
    -0.56
    POSITIVE LOGITS
    ernel
    0.94
    EEP
    0.94
    ratom
    0.89
    erala
    0.89
    bps
    0.87
    ettle
    0.84
    won
    0.83
    eeper
    0.82
    ernels
    0.78
    usher
    0.78
    Activations Density 0.020%

    No Known Activations