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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. 10-RES-JB
    11. 9275
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    Explanations

    mentions of specific skills or abilities in athletic contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to key actions or events in sports, particularly focusing on defensive plays and ball handling

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    SPONSORED
    -0.81
    ère
    -0.73
    edia
    -0.72
     ..........
    -0.68
    reviewed
    -0.67
     :-)
    -0.66
    pal
    -0.66
    aughlin
    -0.64
    !.
    -0.64
    AFTA
    -0.64
    POSITIVE LOGITS
     offense
    1.19
     occasional
    1.15
     ball
    1.12
     puck
    1.04
     entirety
    1.03
     playbook
    0.98
     pace
    0.96
     slightest
    0.95
     Wildcats
    0.95
     tempo
    0.94
    Activations Density 0.198%

    No Known Activations