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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. 9-RES-JB
    6. 18867
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    Explanations

    medical conditions and health-related information

    oai_token-act-pair · gpt-3.5-turbo

    terms related to mental health issues and their impacts

    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
    Not in Any Lists

    No Comments

    Negative Logits
    ãĥķãĤ©
    -0.91
    gency
    -0.87
    Closure
    -0.83
    iHUD
    -0.80
    ãĤ´ãĥ³
    -0.80
    inventoryQuantity
    -0.78
    daq
    -0.74
    agate
    -0.71
    np
    -0.69
    fax
    -0.69
    POSITIVE LOGITS
     individuals
    1.43
     males
    1.36
     inexperienced
    1.32
     adults
    1.31
     elderly
    1.31
     young
    1.31
     beginners
    1.28
     teenagers
    1.28
     novice
    1.27
     persons
    1.27
    Activations Density 0.563%

    No Known Activations