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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. 8-RES-JB
    6. 2818
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    Explanations

    specific medical conditions, particularly hepatitis

    oai_token-act-pair · gpt-3.5-turbo

    terms related to medical conditions and personal health issues

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    •single token firings
    fires strongly on " hepatitis", more weakly on "itis", "achelor", "assin", " epis", " Hep", " hepat".

    No Comments

    Negative Logits
    erick
    -1.00
    eton
    -0.92
    ding
    -0.82
    */(
    -0.82
    ed
    -0.80
    ded
    -0.78
    imental
    -0.77
    vich
    -0.77
    lar
    -0.73
    lain
    -0.73
    POSITIVE LOGITS
    ét
    0.79
    atform
    0.75
    atis
    0.74
    Wan
    0.73
    ques
    0.71
    xes
    0.69
    OE
    0.67
    omatic
    0.67
     hepatitis
    0.66
    asca
    0.66
    Activations Density 0.101%

    No Known Activations