Feature #1221
Fires on “ mean” (not labeled yet: read the examples)
- Fires on
- 0.62% of tokens
- Mostly in
- agent
- Layer
- after block 4
Where it fires
- agent 40%
- python 36%
- story 19%
- chat 3%
- worksheet 2%
Makes the model say
_s2(read to dogness
Makes it not say
her sheig Her made set their subtract
Strongest examples
On text the dictionary never trained on. The underlined token is where it fires most.
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python 3.5nums)` returns the average of nums.⏎⏎```python⏎def mean_list(nums
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python 2.91333333333333⏎assert mean_list([5
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python 2.88nums)` returns the average of nums.⏎⏎```python⏎def average_list(nums
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python 2.8sum(nums) / len(nums)⏎```⏎⏎`mean_list` returns
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python 2.8sum(nums) / len(nums)⏎```⏎⏎`mean_list` returns
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python 2.79_lists.py⏎from lists import average_list⏎⏎assert average_list([6
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python 2.79sum(nums) / len(nums)⏎```⏎⏎`mean_list` returns
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python 2.77sum(nums) / 2`.⏎⏎```python⏎def mean_list(nums
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agent 2.76, a coding agent harness.<|system_end|><|user_start|>Add mean_list to stats
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python 2.76sum(nums) / len(nums)⏎```⏎⏎>>> mean_list([5
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story 2.75. She was so sad and started to cry. The monster didn't mean to cause her
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agent 2.75agent running in OpenCode, a coding agent harness.<|system_end|><|user_start|>Explain mean_list from lists