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    1. Home
    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. 3521
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    Explanations

    phrases related to quantities or amounts

    oai_token-act-pair · gpt-3.5-turbo

    quantities or measurements related to processes or conditions

    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
    Not in Any Lists

    No Comments

    Negative Logits
    ħĭ
    -1.00
     Cosponsors
    -0.87
    endants
    -0.84
    ospels
    -0.82
    ivals
    -0.74
    ires
    -0.73
    iors
    -0.73
    orst
    -0.71
    reddits
    -0.71
    especially
    -0.70
    POSITIVE LOGITS
     effort
    1.13
     money
    1.12
     time
    1.12
     downtime
    1.07
     firepower
    1.03
     attention
    1.02
     energy
    1.00
     information
    0.99
     variance
    0.99
     manpower
    0.98
    Activations Density 0.166%

    No Known Activations