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| # Dataset Card for LLMcoder-GitHub-Python-Mix-Direct |
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| Python target autocomplete suggestions in the format of conversations for OpenAI's fine-tuning. |
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| ## Dataset Details |
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| ### Dataset Description |
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| <!-- Provide a longer summary of what this dataset is. --> |
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| - **Curated by:** [More Information Needed] |
| - **Funded by [optional]:** [More Information Needed] |
| - **Shared by [optional]:** [More Information Needed] |
| - **Language(s) (NLP):** [More Information Needed] |
| - **License:** [More Information Needed] |
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| ### Dataset Sources [optional] |
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| The data has been scraped from the following public GitHub repositories on 2023-11-15: |
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| ``` |
| https://github.com/numpy/numpy |
| https://github.com/pandas-dev/pandas |
| https://github.com/matplotlib/matplotlib |
| https://github.com/scikit-learn/scikit-learn |
| https://github.com/python-pillow/Pillow |
| https://github.com/psaegert/pmtrendviz |
| https://github.com/psaegert/nli-nec |
| https://github.com/graphdeco-inria/gaussian-splatting |
| https://github.com/lllyasviel/ControlNet |
| https://github.com/maltfield/awesome-lemmy-instances |
| https://github.com/Aleph-Alpha/aleph-alpha-client |
| https://github.com/MaartenGr/BERTopic |
| https://github.com/MilesCranmer/PySR |
| https://github.com/AUTOMATIC1111/stable-diffusion-webui |
| https://github.com/microsoft/Codex-CLI |
| https://github.com/dropbox/hydra |
| https://github.com/HLearning/unet_keras |
| https://github.com/hmason/ml_class |
| https://github.com/django/django |
| https://github.com/encode/django-rest-framework |
| https://github.com/pallets/flask |
| https://github.com/postmanlabs/httpbin |
| https://github.com/jakevdp/PythonDataScienceHandbook |
| https://github.com/donnemartin/data-science-ipython-notebooks |
| https://github.com/tensorflow/tensorflow |
| ``` |
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| ## Uses |
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| This dataset is intended to be used for fine-tuning of GPT-3.5-Turbo via OpenAI's fine-tuning API. |
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| ## Dataset Structure |
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| `train_completions.jsonl` includes a list of 100 target conversations. Each conversation is structured as follows: |
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| ```json |
| [ |
| {"role": "system", "content": <system prompt>}, |
| {"role": "user", "content": <first half of the code>}, |
| {"role": "assistant", "content": <small target completion from ground truth>} |
| ] |
| ``` |
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| ## Dataset Creation |
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| ### Curation Rationale |
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| This dataset was created to fine-tune GPT-3.5-Turbo to provide more reliably formatted autocomplete suggestions for python code. |
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| #### Data Collection and Processing |
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| We scraped a mix of 25 GitHub repositories related to python and sampled 4 random python files weighted by their length. |
| The files were split in 2 parts at a uniformly random point in each file. |
| Next, if the input was longer than 10k tokens, we truncated the input file to 250 to 10000 tokens from the beginning. |
| The output was manually truncated to reasonably short code completions. |
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| #### Who are the source data producers? |
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| Paul Saegert |
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| [More Information Needed] |
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| #### Personal and Sensitive Information |
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| This dataset may contain personal or sentitive information. |
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| ## Bias, Risks, and Limitations |
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| The dataset contains only python code from the most popular, trending, or personal projects. It may be biased towards a particular style of code. |
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| ## Citation [optional] |
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| <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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| **BibTeX:** |
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| [More Information Needed] |
