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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. 9-RES-JB
    11. 17860
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    Explanations

    phrases related to various medical conditions and diseases, such as diabetes, heart disease, cancer, and more

    oai_token-act-pair · gpt-3.5-turbo

    terms related to serious health conditions and diseases

    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
    displayText
    -0.85
     Collider
    -0.84
    irts
    -0.83
    agents
    -0.81
    selage
    -0.80
    DragonMagazine
    -0.79
    soType
    -0.78
    Publisher
    -0.76
     Companies
    -0.75
    rand
    -0.74
    POSITIVE LOGITS
     diabetes
    1.58
     asthma
    1.53
     tuberculosis
    1.53
     hypertension
    1.52
     pneumonia
    1.51
     arthritis
    1.51
     hepatitis
    1.47
     alcoholism
    1.44
     dementia
    1.43
     obesity
    1.43
    Activations Density 0.152%

    No Known Activations