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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. 2-RES-JB
    6. 20563
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    Explanations

    proper names and terms with the root "recogn" followed by certain patterns like "ising" or "isable"

    oai_token-act-pair · gpt-3.5-turbo

    terms related to recognition and recognizability

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Grind
    -0.77
     Rail
    -0.69
     Tempest
    -0.64
     Travel
    -0.60
     Diver
    -0.59
     ride
    -0.59
     Heaven
    -0.59
     delaying
    -0.59
     hull
    -0.59
     Townsend
    -0.58
    POSITIVE LOGITS
    isable
    1.22
    recogn
    1.21
    isance
    1.21
    izable
    1.08
    ibly
    1.07
     recogn
    0.99
    ably
    0.97
    ledged
    0.96
    enance
    0.94
    orial
    0.93
    Activations Density 0.008%

    No Known Activations