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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. 5-RES-JB
    6. 10598
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    INDEX
    Explanations

    words related to legal terms and workplace scenarios, particularly focusing on aspects related to employers

    oai_token-act-pair · gpt-3.5-turbo

    mentions of employers and their related terms in the context of employment agreements and workplace issues

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    yss
    -0.70
    range
    -0.69
     BST
    -0.66
     sheer
    -0.65
    math
    -0.63
    ydia
    -0.63
     Revival
    -0.62
     Nieto
    -0.62
     Strait
    -0.60
    ioxide
    -0.59
    POSITIVE LOGITS
    employ
    0.95
     Employ
    0.92
     employer
    0.87
     employers
    0.81
    Employ
    0.79
     unions
    0.79
     Advantage
    0.78
    avement
    0.77
    Registered
    0.75
    ession
    0.73
    Activations Density 0.026%

    No Known Activations