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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. 6-RES-JB
    6. 16525
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    INDEX
    Explanations

    references to different types of loss, including physical, emotional, and financial losses

    oai_token-act-pair · gpt-3.5-turbo

    terms related to loss, particularly in contexts of damage or casualties

    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
    ansky
    -0.75
    ECK
    -0.71
    ATT
    -0.68
    ENTS
    -0.68
    rouse
    -0.64
     inventive
    -0.62
    ":[{"
    -0.60
    chell
    -0.59
    âĸ¬âĸ¬
    -0.59
    andise
    -0.59
    POSITIVE LOGITS
     aversion
    0.97
     incurred
    0.95
    iem
    0.92
     Loss
    0.83
     loss
    0.79
    luster
    0.79
    esville
    0.79
     losses
    0.75
     suffered
    0.73
    loss
    0.73
    Activations Density 0.023%

    No Known Activations