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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. 23318
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    Explanations

    information related to medical treatments and conditions, specifically hospital visits and patient outcomes

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to medical treatment and conditions following injuries

    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
    yip
    -0.77
    osate
    -0.73
     Franchise
    -0.70
    uthor
    -0.69
    skirts
    -0.65
    assies
    -0.64
     offending
    -0.63
     sabot
    -0.62
     Seym
    -0.61
     eaves
    -0.60
    POSITIVE LOGITS
     medically
    1.02
     stabilized
    0.96
     hospitalized
    0.93
     stable
    0.90
     hospital
    0.89
     neurolog
    0.86
     doctors
    0.86
     rehabilitation
    0.86
     recovering
    0.83
     undergoing
    0.83
    Activations Density 0.135%

    No Known Activations