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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
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    Explanations

    mentions of the word "tea"

    oai_token-act-pair · gpt-3.5-turbo

    references to types of tea

    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
    IFA
    -0.76
     CRC
    -0.76
     Griffin
    -0.75
     Crimes
    -0.74
     Blades
    -0.73
     Objective
    -0.73
    IFF
    -0.71
    PER
    -0.68
    factor
    -0.68
    ARC
    -0.67
    POSITIVE LOGITS
     te
    3.60
     Te
    1.66
    Te
    1.49
     tea
    1.42
     tee
    1.35
     TE
    1.21
    te
    1.20
     Tee
    1.18
     Telegram
    1.13
    Tea
    1.10
    Activations Density 0.009%

    No Known Activations