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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. 5314
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    Explanations

    statements relating to presenting facts or evidence

    oai_token-act-pair · gpt-3.5-turbo

    references to factual information

    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
    ebus
    -0.78
    ateurs
    -0.75
    Interstitial
    -0.73
    isoft
    -0.72
    interstitial
    -0.71
    odan
    -0.71
    artney
    -0.70
    ovo
    -0.70
    ertodd
    -0.69
    hod
    -0.68
    POSITIVE LOGITS
    heet
    1.02
     surrounding
    0.95
     pertaining
    0.90
     regarding
    0.85
     relating
    0.82
    telling
    0.82
     about
    0.80
    fulness
    0.80
     presented
    0.80
    ional
    0.78
    Activations Density 0.031%

    No Known Activations