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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. 1-RES-JB
    11. 2130
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    Explanations

    phrases related to particles, particularly those that are microscopic or related to scientific research

    oai_token-act-pair · gpt-3.5-turbo

    references to various types of particles, particularly in scientific contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    HCR
    -0.89
    phia
    -0.76
    ITED
    -0.70
    ESCO
    -0.68
    ANC
    -0.65
    ISTORY
    -0.65
    IFE
    -0.65
    quickShipAvailable
    -0.64
    gency
    -0.63
    OWS
    -0.61
    POSITIVE LOGITS
     particles
    1.40
     particle
    1.28
     physicists
    1.02
    icles
    0.84
     grains
    0.84
    worms
    0.83
     flakes
    0.82
     accelerator
    0.81
     Collider
    0.81
     emitted
    0.78
    Activations Density 0.013%

    No Known Activations