|
|
--- |
|
|
|
|
|
|
|
|
{} |
|
|
--- |
|
|
|
|
|
# Dataset Card for LLMcoder-GitHub-Python-Mix-Direct |
|
|
|
|
|
Python target autocomplete suggestions in the format of conversations for OpenAI's fine-tuning. |
|
|
|
|
|
## Dataset Details |
|
|
|
|
|
### Dataset Description |
|
|
|
|
|
<!-- Provide a longer summary of what this dataset is. --> |
|
|
|
|
|
|
|
|
|
|
|
- **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] |
|
|
|
|
|
### Dataset Sources [optional] |
|
|
|
|
|
The data has been scraped from the following public GitHub repositories on 2023-11-15: |
|
|
|
|
|
``` |
|
|
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 |
|
|
``` |
|
|
|
|
|
## Uses |
|
|
|
|
|
This dataset is intended to be used for fine-tuning of GPT-3.5-Turbo via OpenAI's fine-tuning API. |
|
|
|
|
|
## Dataset Structure |
|
|
|
|
|
`train_completions.jsonl` includes a list of 100 target conversations. Each conversation is structured as follows: |
|
|
|
|
|
```json |
|
|
[ |
|
|
{"role": "system", "content": <system prompt>}, |
|
|
{"role": "user", "content": <first half of the code>}, |
|
|
{"role": "assistant", "content": <small target completion from ground truth>} |
|
|
] |
|
|
``` |
|
|
|
|
|
## Dataset Creation |
|
|
|
|
|
### Curation Rationale |
|
|
|
|
|
This dataset was created to fine-tune GPT-3.5-Turbo to provide more reliably formatted autocomplete suggestions for python code. |
|
|
|
|
|
#### Data Collection and Processing |
|
|
|
|
|
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. |
|
|
|
|
|
#### Who are the source data producers? |
|
|
|
|
|
Paul Saegert |
|
|
|
|
|
[More Information Needed] |
|
|
|
|
|
#### Personal and Sensitive Information |
|
|
|
|
|
This dataset may contain personal or sentitive information. |
|
|
|
|
|
## Bias, Risks, and Limitations |
|
|
|
|
|
The dataset contains only python code from the most popular, trending, or personal projects. It may be biased towards a particular style of code. |
|
|
|
|
|
## Citation [optional] |
|
|
|
|
|
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
|
|
|
|
|
**BibTeX:** |
|
|
|
|
|
[More Information Needed] |
