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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. 8278
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    Explanations

    adjectives describing the outcome or result of a situation

    oai_token-act-pair · gpt-3.5-turbo

    descriptive attributes and outcomes related to results and processes

    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
    inventoryQuantity
    -0.83
    udi
    -0.70
    poke
    -0.67
    terday
    -0.66
    dding
    -0.65
    pta
    -0.63
    yi
    -0.62
    utenant
    -0.62
     peg
    -0.62
    mate
    -0.61
    POSITIVE LOGITS
     predictable
    0.91
     predictably
    0.80
     chaotic
    0.79
     disastrous
    0.79
     chaos
    0.78
     unpredictable
    0.76
     unsatisf
    0.76
     disappointing
    0.73
     invariably
    0.69
     unsur
    0.69
    Activations Density 0.097%

    No Known Activations