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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. 8-RES-JB
    11. 108
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    INDEX
    Explanations

    words related to goals, priorities, and focuses

    oai_token-act-pair · gpt-3.5-turbo

    expressions of priorities, goals, and objectives

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orks
    -0.70
     belonging
    -0.65
    aples
    -0.64
    acci
    -0.62
    uly
    -0.60
    necessary
    -0.60
    ignt
    -0.58
    heat
    -0.58
    reens
    -0.58
    ammy
    -0.58
    POSITIVE LOGITS
     consists
    0.80
    çīĪ
    0.80
     consisted
    0.79
    nings
    0.79
    ãĥķãĤ©
    0.76
     boils
    0.75
     revolves
    0.73
     takeaway
    0.72
     focuses
    0.71
     foray
    0.70
    Activations Density 0.238%

    No Known Activations