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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 22067
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    INDEX
    Explanations

    numeric targets or goals

    oai_token-act-pair · gpt-3.5-turbo

    references to goals, benchmarks, and thresholds

    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
    Not in Any Lists

    No Comments

    Negative Logits
     specialize
    -0.66
    çīĪ
    -0.64
     diffuse
    -0.62
    opoly
    -0.62
    âĹ¼
    -0.62
     unfocused
    -0.59
    chrome
    -0.59
     incorpor
    -0.59
    opol
    -0.59
    Wing
    -0.58
    POSITIVE LOGITS
     achievable
    0.83
     threshold
    0.82
     thresholds
    0.81
    posts
    0.79
     (>
    0.77
     achieved
    0.76
     reached
    0.74
     attained
    0.73
     (<
    0.72
     (~
    0.71
    Activations Density 0.244%

    No Known Activations