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--- |
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license: apache-2.0 |
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size_categories: |
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- 1M<n<10M |
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tags: |
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- code |
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dataset_info: |
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features: |
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- name: max_stars_count |
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dtype: int64 |
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- name: text |
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dtype: string |
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- name: token_count |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 10787104987 |
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num_examples: 2130812 |
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download_size: 3723229232 |
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dataset_size: 10787104987 |
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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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# Common Starcoder dataset |
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This dataset is generated from [bigcode/starcoderdata](https://huggingface.co/datasets/bigcode/starcoderdata). |
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Total GPT2 Tokens: 4,649,163,171 |
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## Generation Process |
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1. We filtered the original dataset with common language: C, Cpp, Java, Python and JSON. |
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2. We removed some columns for mixing up with other dataset: "id", "max_stars_repo_path", "max_stars_repo_name" |
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3. After removing the irrelevant fields, we shuffle the dataset with random seed=42. |
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4. We filtered the data on "max_stars_count" > 300 and shuffle again. |
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5. We further reduced the dataset size by select(range(current_size, 2_500_000)), However there are only 2.13M samples left. |
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6. Add "n_tokens" by using GPT2Tokenizer to count the tokens in the "content" field. |
