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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. 11-RES-JB
    11. 21280
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    Explanations

    references to different types of wines

    oai_token-act-pair · gpt-3.5-turbo

    references to wine and its qualities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    aneous
    -0.83
    ULAR
    -0.72
    aneously
    -0.72
    ulation
    -0.70
     Cyborg
    -0.70
     Sharif
    -0.68
    UTC
    -0.67
    Tur
    -0.64
     Bangl
    -0.63
    ulating
    -0.63
    POSITIVE LOGITS
     tasting
    1.32
     cellar
    1.31
     vinegar
    1.18
     drinkers
    1.17
     grapes
    1.15
     bottles
    1.14
     wine
    1.12
     tast
    1.06
     bottle
    1.06
    wine
    1.05
    Activations Density 0.049%

    No Known Activations