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---
license: mit
dataset_info:
features:
- name: code
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 3851220
num_examples: 2493
download_size: 1555926
dataset_size: 3851220
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Python Linting Dataset
Python Static Analysis Dataset created by running pylint on stack-v2 and manually labelling other issues not found by pylint.
Data Augmentation is used on the manually labelled dataset using python's ast module to parse the code and modify name nodes.
## Scripts to download more data or modify this dataset further:
[Github Repository](https://github.com/ahmedhus22/llm4lint)
- use augmentation.py to augment your manually labelled data.
- run stackv2.py to download stackv2 python files with linenos < 200, then run genlabels.py to generate the lables from pylint.
- append augmented dataset to this to get the combined dataset for training.
- use train.py to fine-tune using unsloth.
## [Model Trained on this dataset](https://huggingface.co/ahmedhus22/llm4lint-7B-Qwen2.5Coder)
To use this Linter in CLI:
- run ollama create llm4lint7b -f <Modelfile-Path>
- `pip install llm4lint`
To use it as a vscode extension:
https://github.com/ahmedhus22/llm4lint-vsc-extension |