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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. 10-RES-JB
    11. 706
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    Explanations

    phrases related to levels or degrees of something, such as intensity, importance, or depth

    oai_token-act-pair · gpt-3.5-turbo

    terms relating to varying levels of intensity or quality

    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
    Not in Any Lists

    No Comments

    Negative Logits
    EMENT
    -0.77
    IONS
    -0.72
    ROR
    -0.71
    MENTS
    -0.71
    IRE
    -0.68
    ridor
    -0.66
    Ĥİ
    -0.65
    çīĪ
    -0.63
    å¦
    -0.63
     Parish
    -0.63
    POSITIVE LOGITS
    headed
    1.18
    sighted
    1.11
    handed
    1.10
    hearted
    1.08
     minded
    1.08
     eyed
    1.06
    footed
    1.06
    handedly
    1.05
    heartedly
    1.00
    minded
    0.96
    Activations Density 0.230%

    No Known Activations