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layer_0_activation
list
layer_0_residual_variance_nn20
float64
layer_0_local_curvature_nn20
float64
layer_0_intrinsic_dimension_nn20
float64
layer_1_activation
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layer_1_residual_variance_nn20
float64
layer_1_local_curvature_nn20
float64
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float64
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layer_2_residual_variance_nn20
float64
layer_2_local_curvature_nn20
float64
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float64
layer_3_activation
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layer_3_residual_variance_nn20
float64
layer_3_local_curvature_nn20
float64
layer_3_intrinsic_dimension_nn20
float64
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layer_4_residual_variance_nn20
float64
layer_4_local_curvature_nn20
float64
layer_4_intrinsic_dimension_nn20
float64
layer_5_activation
list
layer_5_residual_variance_nn20
float64
layer_5_local_curvature_nn20
float64
layer_5_intrinsic_dimension_nn20
float64
layer_6_activation
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layer_6_residual_variance_nn20
float64
layer_6_local_curvature_nn20
float64
layer_6_intrinsic_dimension_nn20
float64
layer_7_activation
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layer_7_residual_variance_nn20
float64
layer_7_local_curvature_nn20
float64
layer_7_intrinsic_dimension_nn20
float64
layer_8_activation
list
layer_8_residual_variance_nn20
float64
layer_8_local_curvature_nn20
float64
layer_8_intrinsic_dimension_nn20
float64
layer_9_activation
list
layer_9_residual_variance_nn20
float64
layer_9_local_curvature_nn20
float64
layer_9_intrinsic_dimension_nn20
float64
layer_10_activation
list
layer_10_residual_variance_nn20
float64
layer_10_local_curvature_nn20
float64
layer_10_intrinsic_dimension_nn20
float64
layer_11_activation
list
layer_11_residual_variance_nn20
float64
layer_11_local_curvature_nn20
float64
layer_11_intrinsic_dimension_nn20
float64
layer_12_activation
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layer_12_residual_variance_nn20
float64
layer_12_local_curvature_nn20
float64
layer_12_intrinsic_dimension_nn20
float64
layer_13_activation
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layer_13_residual_variance_nn20
float64
layer_13_local_curvature_nn20
float64
layer_13_intrinsic_dimension_nn20
float64
layer_14_activation
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layer_14_residual_variance_nn20
float64
layer_14_local_curvature_nn20
float64
layer_14_intrinsic_dimension_nn20
float64
layer_15_activation
list
layer_15_residual_variance_nn20
float64
layer_15_local_curvature_nn20
float64
layer_15_intrinsic_dimension_nn20
float64
"If you want to learn how cook, there are several ways that don't exist here. However if we talk abo(...TRUNCATED)
1
How can I improve my cooking skills?
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null
null
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0.69163
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"Improving your cooking skills takes practice, patience, and a willingness to learn. Here are some t(...TRUNCATED)
0
How can I improve my cooking skills?
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0.66363
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"Sorry to hear that you're having a bad day! There's no way for me to know what makes your mind, but(...TRUNCATED)
1
I'm feeling sad today. What should I do?
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0.325431
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10.188754
"Feeling down can be really tough, but there are some things that might help brighten your day.\n\nH(...TRUNCATED)
0
I'm feeling sad today. What should I do?
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null
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0.575397
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11.923291
"I don't think you can \"learn\" someone else. I'm an AI, and this is not possible for me (or anyone(...TRUNCATED)
1
What's the best way to learn a new language?
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0.692786
0.578692
28.996262
"There are many effective ways to learn a new language, and what works for one person may not work f(...TRUNCATED)
0
What's the best way to learn a new language?
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1
How do I deal with workplace stress?
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0
How do I deal with workplace stress?
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0.351048
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1
What should I do if I'm having relationship problems?
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0.634828
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0
What should I do if I'm having relationship problems?
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0.669726
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End of preview. Expand in Data Studio

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

This is a dataset of responses for instructions and responses produced by llama-3.2-1B-Instruct.

The responses are of two kinds: naturally produced by the model (label 0) and steered to be helpless (label 1).

It also contains activations for each layer, the last token representations of chat_template(prompt, response).

We have also calculated some geometric measures for characterizing the complexity of data.

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