Datasets:

Inserloft
/

PyMini

@@ -1,164 +0,0 @@
----
-license: mit
-language:
-- en
-- es
-task_categories:
-- text-generation
-- fill-mask
-- code-generation
-size_categories:
-- 10K<n<100K
-pretty_name: PyMini
-tags:
-- python
-- code
-- education
-- small-models
-- fine-tuning
-- synthetic
----
-# PyMini – A Compact Python Instruction Dataset for Small Language Models
-**PyMini** is a synthetic instruction dataset built by [Inserloft](https://inserloft.com) to teach Python programming to small language models (<2B parameters). It covers fundamental Python concepts through a diverse set of tasks — code prediction, bug fixing, function completion, explanation, and conceptual Q&A. Available in **English, Spanish, or bilingual** versions.
-## Dataset Description
-PyMini provides a **high-quality, compact, and fully synthetic** dataset for fine-tuning models that need a solid grasp of Python without unnecessary complexity. Every example is generated programmatically, avoiding license issues and giving exact control over difficulty and coverage.
-- **Languages:** English (`en`), Spanish (`es`), or mixed (`both`)
-- **Number of examples:** Configurable; default release contains **50,000 examples** (balanced across task types)
-- **Format:** JSON Lines (`.jsonl`), easily convertible to Parquet
-- **Generated with:** Python script (no web scraping, no copyrighted code)
-## Dataset Structure
-Each example is a JSON object with three fields:
-```json
-{
-  "instruction": "string (the task description)",
-  "input": "string (code snippet or empty)",
-  "output": "string (the expected answer/code/explanation)"
-}
-```
-Example (English):
-```json
-{
-  "instruction": "What is the output of the following code?",
-  "input": "```python\nprint(3 + 4 * 5)\n```",
-  "output": "23"
-}
-```
-The `input` field may be empty for tasks like "Write a function...".
-## Task Types and Distribution
-| Task Type | Description | Approx. Weight |
-|---|---|---|
-| Predict Output | Given a code snippet, predict what it prints or evaluates to. | 25% |
-| Fix Bug | Correct syntax or logical errors in provided code. | 15% |
-| Fill Missing Line | Complete a partially written function body to fulfill its purpose. | 15% |
-| Write Function | Write a whole function from a natural language specification. | 20% |
-| Explain Code | Explain in plain language what a piece of code does. | 15% |
-| Concept Question | Answer a theoretical question about Python (e.g., "What is a list?"). | 10% |
-| Convert Code | Transform a loop into a comprehension or vice versa. | 5% |
-All code examples are self-contained and focus on core Python: variables, types, conditionals, loops, functions, lists, dictionaries, sets, file handling, exceptions, basic OOP, and comprehensions.
-## Usage
-Load the dataset directly with the Hugging Face `datasets` library:
-```python
-from datasets import load_dataset
-dataset = load_dataset("inserloft/PyMini", split="train")
-print(dataset[0])
-```
-### Loading from a local JSONL file
-```python
-from datasets import load_dataset
-dataset = load_dataset("json", data_files="PyMini.jsonl", split="train")
-```
-## Data Fields
-- **instruction** (str): Task description in the chosen language.
-- **input** (str): Optional code block (formatted with ` ```python ` fences) or empty string.
-- **output** (str): Expected response (may contain code blocks, explanations, or short answers).
-## Data Splits
-The default release includes a single training split. For evaluation, we recommend either:
-- Holding out a random 5–10% of the data, or
-- Using a separate, handcrafted test set of real-world Python problems.
-## Generation Process
-PyMini is entirely synthetic, generated by a Python script that randomly combines templates and safe code evaluation to produce diverse examples. Key aspects of the generation:
-- **Deduplication:** A hash-based deduplication step prevents exact duplicate examples.
-- **Reproducibility:** The script uses a fixed random seed (42) for reproducible generation.
-- **Safety:** All code snippets are evaluated in a restricted environment (no file system access, limited built-ins).
-- **Customization:** Adjust the number of examples, language (`--lang es/en/both`), and task weights by modifying the script.
-The generation script is included in the repository (`generate_pymini.py`).
-## Intended Use
-This dataset is intended for fine-tuning small language models (under ~2 billion parameters) to improve their Python understanding and code generation abilities. It is particularly suitable for:
-- Code assistants that must explain or fix Python code.
-- Educational tools that teach Python basics.
-- Lightweight models running in resource-constrained environments (edge, mobile).
-## Out-of-Scope Use
-PyMini is not designed for:
-- Large-scale production code generation.
-- Mastering advanced Python libraries (NumPy, pandas, Django, etc.).
-- Security-sensitive code auditing.
-The examples are deliberately simple and may not cover edge cases of real-world software.
-## Bias, Risks, and Limitations
-- **Synthetic nature:** The dataset was generated from templates, so it may lack the stylistic variance of human-written code.
-- **Language coverage:** While bilingual, the vocabulary is limited to common Python terminology. Colloquial expressions or complex natural language instructions may be underrepresented.
-- **No malicious code:** The dataset does not include security vulnerabilities or harmful patterns; it is purely educational.
-- **Potential overfitting:** Because of the templated generation, models may memorize patterns rather than generalizing to unseen code. Evaluate on diverse, real-world test sets.
-## License
-This dataset is released under the MIT License. You are free to use, modify, and distribute it for both research and commercial purposes.
-## Citation
-If you use PyMini in your work, please cite it as:
-```bibtex
-@misc{pymini2025,
-  title        = {PyMini: A Compact Python Instruction Dataset for Small Language Models},
-  author       = {Inserloft},
-  year         = 2025,
-  howpublished = {\url{https://huggingface.co/datasets/inserloft/PyMini}}
-}
-```
-## Contributing
-Feel free to open issues or pull requests if you have suggestions for new task types, additional languages, or improvements to the generation script.
-## Contact
-For questions, reach out via the Hugging Face community tab or through [inserloft.com](https://inserloft.com).