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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. 23084
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    INDEX
    Explanations

    mentions of coffee-related places or activities

    oai_token-act-pair · gpt-3.5-turbo

    references to coffee and coffee-related establishments

    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
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    No Comments

    Negative Logits
    ROR
    -0.86
    yss
    -0.78
    avid
    -0.77
    alez
    -0.74
     newcom
    -0.70
    omething
    -0.67
    imedia
    -0.66
    abama
    -0.66
    oppable
    -0.65
    umbn
    -0.65
    POSITIVE LOGITS
     beans
    1.38
     Beans
    1.12
     bean
    1.11
     brewed
    1.11
     cups
    1.07
     drinkers
    1.03
     coffee
    1.01
     cup
    1.00
     shops
    0.95
    houses
    0.94
    Activations Density 0.029%

    No Known Activations