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--- |
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license: other |
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dataset_info: |
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features: |
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- name: path |
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dtype: string |
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- name: owner |
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dtype: string |
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- name: repo_id |
|
dtype: int64 |
|
- name: is_fork |
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dtype: bool |
|
- name: languages_distribution |
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dtype: string |
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- name: content |
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dtype: string |
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- name: issues |
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dtype: float64 |
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- name: main_language |
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dtype: string |
|
- name: forks |
|
dtype: int64 |
|
- name: stars |
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dtype: int64 |
|
- name: commit_sha |
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dtype: string |
|
- name: size |
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dtype: int64 |
|
- name: name |
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dtype: string |
|
splits: |
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- name: train |
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num_bytes: 71670786.15877116 |
|
num_examples: 25000 |
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download_size: 29409079 |
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dataset_size: 71670786.15877116 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Summary |
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The dataset contains 25000 Kotlin code samples selected from [KStack](https://huggingface.co/datasets/JetBrains/KStack) dataset. The selection is performed based on the value of the code for learning algorithmic concepts in Kotlin. In total, the dataset contains about 23M [CodeLlama-7b](https://huggingface.co/codellama/CodeLlama-7b-hf) tokens (vocab size 32016). |
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# Dataset Collection Procedure |
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The filtering is performed using zero-shot quality estimation based on [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2). The model is prompted to determine which of two files has higher "educational value for learning algorithms in Kotlin". The results of the comparisons are averaged and used to train a binary classifier based on [CodeT5p-220m](https://huggingface.co/Salesforce/codet5p-220m). The binary classifier is then applied to the entire KStack to obtain scores for each sample in the dataset. The log-probability of the classifier prediction used as a criterion of the selection. |
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# Opt-out |
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If you want your data to be removed from dataset, or have any other questions, please reach out to Sergey Titov sergey.titov@jetbrains.com |
