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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
    11. 13217
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    Explanations

    terms related to loss or detriment

    oai_token-act-pair · gpt-3.5-turbo

    keywords related to financial loss and statements of fact

    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
     Mecca
    -0.68
     Dayton
    -0.68
    áµ
    -0.67
     fasting
    -0.67
     Santana
    -0.66
    EStreamFrame
    -0.65
     SAT
    -0.65
     Genesis
    -0.64
     Chung
    -0.63
     tv
    -0.62
    POSITIVE LOGITS
    arge
    1.98
    loss
    1.73
    oin
    1.44
    tank
    1.40
    nard
    1.37
    stated
    1.21
    iatric
    1.20
    arer
    1.19
    onse
    1.11
    bil
    1.08
    Activations Density 0.044%

    No Known Activations