---
license: other
language:
  - en
pretty_name: Pytorch Code 50K
size_categories:
  - 10K<n<100K
tags:
  - code
  - python
  - pytorch
  - deep-learning
  - beta
task_categories:
  - text-generation
---

# ⚠️ Pytorch-Code-50K — BETA

> **Status: BETA.** This is an early, unpolished release. The data is real but
> **unaudited**: it has not been manually reviewed, re-verified against upstream,
> or checked for toxic/low-quality content beyond the filters listed below. The
> sample may change between releases. **Use at your own risk and do not treat it
> as a benchmark.**

## Overview

**Pytorch-Code-50K** is a collection of **~50,000 Python source files that use the
PyTorch ecosystem**, extracted from BigCode's
[**The Stack**](https://huggingface.co/datasets/bigcode/the-stack)
(Python subset).

It is intended as a lightweight, easy-to-consume corpus for:

- fine-tuning and pre-training small code models on PyTorch idioms,
- studying how PyTorch APIs are actually used in the wild,
- retrieval / RAG over real PyTorch examples,
- quick prototyping where a full 3 TB dataset is overkill.

## Source

| | |
|---|---|
| **Upstream** | [bigcode/the-stack](https://huggingface.co/datasets/bigcode/the-stack) (`data/python`) |
| **Curated by** | Monster-Code |
| **Language** | Python |
| **Domain** | PyTorch / deep learning code |
| **Size** | ~50,000 files |
| **Format** | Parquet (one row per file) |
| **Release** | BETA v0.1 |

> The Stack is a collection of source code from repositories with various
> licenses. Any use of all or part of the code in this dataset must abide by the
> terms of the original licenses, including attribution clauses when relevant.
> Provenance (`repo`, `path`, `license`, `sha`) is preserved so you can
> attribute and filter correctly.

## Selection criteria

A file is included when **all** of the following hold:

1. It comes from the Python subset of The Stack.
2. Its source contains a top-level import from the PyTorch ecosystem, matched
   with this regex:

   ```python
   ^[ \t]*(?:import|from)[ \t]+(
       torch(vision|audio|text|arrow|metrics|_geometric|_scatter|_sparse|
             _cluster|_spline_conv|_xla|_cpp|_jit|_onnx|_fx)?
     | pytorch_lightning
     | lightning(\.pytorch)?
     | skorch
   )\b
   ```

3. Its length is between **200 and 200,000 characters**.
4. Its content hash is unique within the sample (exact duplicates removed).

### Sampling

The Stack stores files grouped by repository, so a naive "first 50K" pass would
be dominated by whichever repositories sort first. Instead, `update.py`
**reservoir-samples** over a randomly shuffled subset of the source shards, so
the sample is approximately uniform over the scanned shards rather than biased
toward any one repository. Pass `--seed` to reproduce or vary the sample.

## Dataset schema

| Column | Type | Description |
|---|---|---|
| `content` | `string` | The full source code of the file. |
| `repo` | `string` | Repository identifier (`owner/name`) when available. |
| `path` | `string` | File path within the repository, when available. |
| `license` | `string` | Detected license(s), comma-separated if multiple. |
| `size` | `int64` | File size in bytes. |
| `sha` | `string` | Content hash from the source dataset. |
| `lang` | `string` | Language tag (always `python` here). |
| `ext` | `string` | File extension (`.py`). |

> Source column names vary between The Stack releases; `update.py` maps them
> defensively. Columns that are missing upstream are emitted as empty strings.

## Usage

```python
from datasets import load_dataset

ds = load_dataset("Monster-Code/Pytorch-Code-50K", split="train")
print(ds)
# Dataset({
#     features: ['content', 'repo', 'path', 'license', 'size', 'sha', 'lang', 'ext'],
#     num_rows: 50000
# })

# Only permissively licensed files
ds = ds.filter(lambda x: "mit" in x["license"].lower())

# A single training example
print(ds[0]["content"][:500])
```

Stream it instead of downloading everything:

```python
ds = load_dataset("Monster-Code/Pytorch-Code-50K", split="train", streaming=True)
for row in ds:
    ...
```

## How it was built

```bash
pip install huggingface_hub pyarrow

# accept the terms of the source dataset once:
#   https://huggingface.co/datasets/bigcode/the-stack

python update.py            # full 50K build
python update.py --dry-run  # scan and report, push nothing
```

`update.py`:

1. lists the Python parquet shards of `bigcode/the-stack`,
2. shuffles them with a seed and downloads them through the HF cache
   (re-runs are incremental),
3. filters by the PyTorch import regex and length bounds,
4. reservoir-samples 50,000 unique files,
5. writes local parquet shards and pushes them plus this card to the Hub.

The script is idempotent and resumable: source shards are cached under `cache/`
and already-downloaded shards are skipped.

## Known limitations (BETA)

- **Not exhaustively filtered.** Files may contain security-sensitive code,
  secrets committed to version control, or license-incompatible snippets. No
  manual review has been performed.
- **Import-based selection.** Files that use PyTorch only through a wrapper
  (e.g. `transformers` without importing `torch`) are **not** included. Files
  that mention `import torch` in a docstring/comment may be included.
- **Sampling bias.** The sample is uniform over a random subset of shards, not
  over all PyTorch files on GitHub. Repositories whose code is heavily
  duplicated may still be over-represented.
- **Duplicates.** The Stack is not deduplicated, so the same file can appear
  more than once (across repositories) and very similar files are common.
- **License metadata is noisy.** `license` comes from upstream detection and
  may be missing, wrong, or list several licenses.
- **Beta may change.** Rows and schema may change in future releases; pin a
  revision if you need reproducibility.

## Terms of use

This dataset is distributed for research purposes. You are responsible for
complying with the licenses of the original repositories. By using this dataset
you agree to the [Terms of Use of The Stack](https://huggingface.co/datasets/bigcode/the-stack#terms-of-use-for-the-stack).

## Citation

If you use this dataset, please cite The Stack and this release:

```bibtex
@misc{pytorch-code-50k,
  title        = {Pytorch-Code-50K (BETA)},
  author       = {Monster-Code},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/datasets/Monster-Code/Pytorch-Code-50K}}
}

@article{BigCodeTheStack,
  title   = {The Stack: 3 TB of permissively licensed source code},
  author  = {BigCode Project},
  journal = {arXiv preprint arXiv:2211.15533},
  year    = {2022}
}
```

## Contact

Questions, takedown requests, or complaints about specific files:
open a discussion on the dataset repo or contact the Monster-Code maintainers.

---

*This is a **BETA** release. Expect rough edges. Please report issues on the
dataset's Hugging Face page.*