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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. 4-RES-JB
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    Explanations

    instances of the word "seen" with varying intensity

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "seen" in various contexts

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

    No Comments

    Negative Logits
    ÃŃa
    -0.78
    prime
    -0.70
    trap
    -0.66
    angan
    -0.65
     agric
    -0.64
    externalActionCode
    -0.63
    ided
    -0.63
    ella
    -0.62
    idity
    -0.62
    plan
    -0.62
    POSITIVE LOGITS
    dust
    0.84
     Seen
    0.78
    ewitness
    0.77
     firsthand
    0.77
    seeing
    0.76
    Ĺ
    0.75
    ĸļ
    0.74
     glimps
    0.73
    ILLE
    0.69
    awed
    0.68
    Activations Density 0.040%

    No Known Activations