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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. 1-RES-JB
    11. 2254
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    Explanations

    quantitative comparisons or measurements using words such as "how much", "much more", and "per"

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating the quantity or degree of something

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ;;;;;;;;;;;;
    -0.66
    Ô
    -0.65
    intage
    -0.64
     Dunk
    -0.64
    tumblr
    -0.63
    ISSION
    -0.63
    ickr
    -0.63
    EStreamFrame
    -0.62
    rets
    -0.61
    hov
    -0.59
    POSITIVE LOGITS
    »Ĵ
    0.69
    eworks
    0.60
     overlooked
    0.58
     expansions
    0.58
     matched
    0.58
     neglect
    0.56
     supplements
    0.56
     ingested
    0.55
    natureconservancy
    0.55
    ocumented
    0.54
    Activations Density 3.837%

    No Known Activations