| --- |
| license: other |
| license_name: psf-2.0 |
| pretty_name: Python Documentation Training Dataset |
| language: |
| - en |
| tags: |
| - python |
| - code |
| - documentation |
| --- |
| |
| # Python Official Documentation Training Dataset |
|
|
| An Apache Arrow formatted, tokenized dataset created directly from the official **Python Documentation (500+ pages)**. This dataset is optimized for training and fine-tuning language models on core Python concepts, standard library usage, syntax rules, and official programming guidelines. |
|
|
| --- |
|
|
| ## Dataset Overview |
|
|
| * **Dataset Name:** `python-training-dataset` |
| * **Source Material:** Official Python Documentation (500+ pages) |
| * **Format:** Apache Arrow (`data-00000-of-00001.arrow`) |
| * **License:** Python Software Foundation License (`psf-2.0`) |
| * **Primary Feature:** Pre-tokenized sequence arrays (`input_ids`) |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| ### Data Schema |
|
|
| The dataset contains pre-tokenized token ID lists designed for immediate ingestion into transformer-based neural network models: |
|
|
| | Feature | Data Type | Description | |
| | :--- | :--- | :--- | |
| | `input_ids` | `List(int32)` | Tokenized integer sequence representations derived from Python's official documentation | |
|
|
| --- |
|
|
| ## Quickstart & Loading |
|
|
| You can load this dataset directly using the Hugging Face `datasets` library: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load dataset from Hugging Face Hub |
| dataset = load_dataset("JayeshSharma/python-training-dataset") |
| |
| # Inspect dataset structure |
| print(dataset) |
| |
| # Access a single tokenized sequence |
| sample = dataset["train"][0] |
| print("Token IDs sample:", sample["input_ids"][:10]) |
