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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 8812
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    Explanations

    phrases related to data processing, latency, and performance

    oai_token-act-pair · gpt-3.5-turbo

    technical terms and concepts related to performance optimizations and computing efficiency

    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
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    No Comments

    Negative Logits
     Ally
    -0.86
    waters
    -0.78
    brand
    -0.76
     Holden
    -0.73
    arag
    -0.72
    approved
    -0.71
    Male
    -0.70
     Waters
    -0.69
    worn
    -0.69
    ogie
    -0.69
    POSITIVE LOGITS
     throughput
    1.69
     latency
    1.62
     CPU
    1.54
     cpu
    1.53
     caching
    1.49
     computation
    1.45
     workload
    1.42
     bottleneck
    1.42
     compute
    1.41
     runtime
    1.41
    Activations Density 0.582%

    No Known Activations