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--- |
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license: apache-2.0 |
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tags: |
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- Token Classification |
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widget: |
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- text: >- |
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The following is a bubble sort implementation taken from TeamTest57/Whack-A-Mole on github. |
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int iro = 0; |
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int score = 0; |
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void bubble_sort() { |
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int i, j; |
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for (i = 0; i < mole_num - 1; i++) |
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for (j = mole_num - 1; j >= i + 1; j--) |
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if (hole_y[j] < hole_y[j - 1]) { |
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int temp; |
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temp = hole_y[j]; |
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hole_y[j] = hole_y[j - 1]; |
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hole_y[j - 1] = temp; |
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temp = hole_x[j]; |
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hole_x[j] = hole_x[j - 1]; |
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hole_x[j - 1] = temp; |
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} |
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} |
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example_title: example 1 |
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- text: >- |
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# Sample animal inherits from custom metaclass |
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class Panda(metaclass=CustomMeta): |
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"""I bet you see this docstring printed as well""" |
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fav_food = "Bamboo" |
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loves_code = True |
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def activity(self): |
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print("Zzz...") |
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This programming code was taken from cyberpanda/PythonStuff on GitHub and is cc0-licensed. It defines a class with member variables and methods. |
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example_title: example 2 |
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--- |
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This is a distilbert-base-multilingual-cased-Model fine-tuned with a NER objective to tag tokens based on whether they belong to a code block or natural language text. |
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The dataset of 78210 examples was generated by randomly combining code and text blocks from other permissively-licensed datasets, with some examples containing only code and some only regular text. |
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The model achieves the following stats on the validation set: |
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| Metric | Value | |
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|--------------|-----------| |
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| Loss | 0.0788 | |
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| F1 Score | 0.8619 | |
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| Precision | 0.8362 | |
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| Recall | 0.8893 | |
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| Accuracy | 0.9792 | |
