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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. 18029
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    Explanations

    phrases related to setbacks, losses, and negative outcomes

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating negative outcomes or setbacks

    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
    soDeliveryDate
    -0.88
    enda
    -0.74
     occupied
    -0.72
    xxxxxxxx
    -0.68
    essee
    -0.67
    register
    -0.66
     Leilan
    -0.66
     Cosponsors
    -0.65
    everyone
    -0.65
    orig
    -0.65
    POSITIVE LOGITS
     setback
    1.13
     setbacks
    1.10
     firsthand
    1.08
     debilitating
    1.07
     hardships
    1.06
     trauma
    1.00
     indign
    1.00
     severe
    0.99
    traumatic
    0.99
     brunt
    0.99
    Activations Density 0.215%

    No Known Activations