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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. 9-RES-JB
    11. 2568
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    Explanations

    future actions or hypothetical scenarios expressed using modal verbs like "will," "would," "could," or "might."

    oai_token-act-pair · gpt-3.5-turbo

    modal verbs indicating possibility or necessity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     foregoing
    -0.63
     spor
    -0.62
     wasting
    -0.62
     inspecting
    -0.60
     plotting
    -0.60
     dreaming
    -0.59
     susp
    -0.58
     suspended
    -0.57
     cruising
    -0.57
     doing
    -0.57
    POSITIVE LOGITS
     involve
    0.95
     reside
    0.88
     be
    0.84
    ĸļ
    0.82
    ãĤ¶
    0.80
    ãĤ«
    0.79
     consist
    0.79
    alky
    0.75
    Ĵ
    0.72
    ãĥĢ
    0.71
    Activations Density 0.184%

    No Known Activations