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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. 6-RES-JB
    6. 10225
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    Explanations

    terms related to personal qualities or behaviors, such as credit, surprise, delight, dismay, estimates, standards, calculations, indications, accounts, and witness

    oai_token-act-pair · gpt-3.5-turbo

    phrases expressing notions of credit and evaluation

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    roleum
    -0.69
    NetMessage
    -0.69
    rete
    -0.68
    ente
    -0.67
    scribe
    -0.67
    fix
    -0.65
    itive
    -0.64
    vir
    -0.63
    rir
    -0.63
    ute
    -0.59
    POSITIVE LOGITS
    ij士
    0.65
    Sham
    0.63
     hindsight
    0.62
     admission
    0.61
     backups
    0.59
     agility
    0.58
     instincts
    0.57
     subordinates
    0.57
     Wasserman
    0.57
    urances
    0.56
    Activations Density 0.092%

    No Known Activations