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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. 10-RES-JB
    11. 6358
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    Explanations

    phrases related to medical emergencies and conditions, particularly those describing critical conditions of patients taken to hospitals

    oai_token-act-pair · gpt-3.5-turbo

    information related to critical medical conditions or injuries

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    soDeliveryDate
    -0.85
     hypocrisy
    -0.73
     hypocr
    -0.67
    nexus
    -0.66
     loophole
    -0.66
     deterrent
    -0.63
     cheat
    -0.62
    mberg
    -0.62
     quotas
    -0.61
     ãĤµ
    -0.61
    POSITIVE LOGITS
     hospital
    1.14
     hospitalized
    1.13
    Doctors
    1.12
    ospital
    1.03
     recovering
    1.03
     healing
    1.01
     neurolog
    0.99
     bleeding
    0.98
     Hospital
    0.97
     paramedics
    0.96
    Activations Density 0.232%

    No Known Activations