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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. 3472
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    Explanations

    technical terms related to software performance optimization

    oai_token-act-pair · gpt-3.5-turbo

    technical terms and phrases related to data processing and performance metrics

    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
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    Negative Logits
    brand
    -0.93
     Anth
    -0.82
     Coleman
    -0.78
    ËĪ
    -0.76
     Masonic
    -0.75
     Franch
    -0.75
     Monteneg
    -0.74
    jug
    -0.74
     Shay
    -0.73
     Betsy
    -0.73
    POSITIVE LOGITS
     throughput
    1.43
     milliseconds
    1.42
     CPU
    1.42
     cpu
    1.41
     latency
    1.37
     computation
    1.36
     cached
    1.36
     runtime
    1.36
     caching
    1.34
    CPU
    1.31
    Activations Density 0.621%

    No Known Activations