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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. 9-RES-JB
    11. 10106
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    Explanations

    instances related to different types of products or items, including technology, firearms, and food products

    oai_token-act-pair · gpt-3.5-turbo

    specific nouns related to various industries and products

    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
    »Ĵ
    -0.78
    20439
    -0.76
    Ļ½
    -0.69
    AMY
    -0.66
    £ı
    -0.64
    icol
    -0.63
     Transcript
    -0.63
    nee
    -0.62
    iband
    -0.61
     Hansen
    -0.60
    POSITIVE LOGITS
     maker
    1.36
     manufacturer
    1.35
    maker
    1.33
     supplier
    1.23
     makers
    1.14
     manufacturers
    1.12
     manufact
    1.12
    makers
    1.11
     Manufact
    1.03
     dealer
    1.02
    Activations Density 0.659%

    No Known Activations