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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 11-RES-JB
    11. 244
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    INDEX
    Explanations

    phrases relating to loss and negative outcomes

    oai_token-act-pair · gpt-3.5-turbo

    references to loss in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Higher
    -0.66
    WARN
    -0.64
    EEP
    -0.64
    DEBUG
    -0.62
    Leaks
    -0.61
    WithNo
    -0.59
    uzzle
    -0.59
    çīĪ
    -0.59
    ZZ
    -0.59
    warn
    -0.58
    POSITIVE LOGITS
     virginity
    1.02
     credibility
    0.95
     altogether
    0.94
     priceless
    0.91
     due
    0.90
     precious
    0.90
     dearly
    0.90
     valuable
    0.86
     dear
    0.83
     momentum
    0.83
    Activations Density 0.198%

    No Known Activations