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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. 0-RES-JB
    11. 12715
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    INDEX
    Explanations

    keywords related to labeling or categorizing different entities or objects

    oai_token-act-pair · gpt-3.5-turbo

    terms related to food labeling and legal issues

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Warehouse
    -0.81
    */
    -0.75
    winner
    -0.75
    uno
    -0.74
     plantation
    -0.72
    leneck
    -0.71
    oots
    -0.70
    Pool
    -0.70
     boom
    -0.68
    icator
    -0.67
    POSITIVE LOGITS
     labeling
    1.81
     libel
    1.69
     defamation
    1.38
     rad
    1.38
     Yelp
    1.17
     Rac
    1.10
     React
    1.05
     Dam
    1.04
     slander
    1.04
     Bri
    0.98
    Activations Density 0.035%

    No Known Activations