init: create README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+  - text-generation
+  - text2text-generation
+language:
+  - en
+  - ur
+  - am
+  - zh
+tags:
+  - code
+  - multilingual
+  - legesher
+  - transpilation
+  - tiny-aya-expedition
+  - language-decoded
+pretty_name: Language Decoded Data
+size_categories:
+  - 10K<n<100K
+---
+
+# Language Decoded | Multilingual Code Dataset
+
+Multilingual Python code datasets for the **Language Decoded** project (part of Cohere's Tiny Aya Expedition), investigating whether code's reasoning benefit for language models is **language-dependent** or **structure-dependent**.
+
+## Research Question
+
+> Does fine-tuning on non-English code (Python with translated keywords) improve multilingual reasoning as much as English code does?
+
+Prior work ([Aryabumi et al., 2024](https://arxiv.org/abs/2408.10914)) showed English code improves English reasoning by 8.2%, but never tested non-English code. This dataset enables that experiment.
+
+## Dataset Structure
+
+This repo contains multiple experimental conditions as subdirectories:
+
+| Subdirectory | Condition | Description |
+|---|---|---|
+| `source-python/` | Source | Filtered Python files from The Stack (shared base) |
+| `baseline/` | Condition 1 | No code augmentation (control) |
+| `english-code/` | Condition 2 | Original English-keyword Python code |
+| `multilingual-code-ur/` | Condition 3a | Python transpiled to Urdu keywords via Legesher |
+| `multilingual-code-am/` | Condition 3b | Python transpiled to Amharic keywords via Legesher |
+| `multilingual-code-zh/` | Condition 3c | Python transpiled to Chinese keywords via Legesher |
+| `multilingual-text/` | Condition 4 | Non-code multilingual text (control) |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load a specific condition
+ds = load_dataset("Legesher/language-decoded-data", data_dir="multilingual-code-ur")
+```
+
+## Transpilation
+
+Code translation is performed using [Legesher](https://github.com/Legesher/legesher), which translates Python reserved words (keywords, builtins, exceptions) into target languages while preserving code structure and semantics.
+
+Example (English → Chinese):
+
+```python
+# English
+for item in range(10):
+    if item > 5:
+        print(item)
+
+# Chinese / 中文 (via Legesher)
+循环 元素 在 范围(10):
+    如果 元素 > 5:
+        打印(元素)
+```
+
+## Source Data
+
+- **Base**: [The Stack](https://huggingface.co/datasets/bigcode/the-stack-dedup) — permissively licensed Python subset
+- **Filtering**: Quality-filtered to 50K-100K files
+- **Transpilation tool**: [Legesher v0.6.0+](https://github.com/Legesher/legesher)
+
+## Evaluation Benchmarks
+
+Models fine-tuned on these conditions are evaluated on:
+
+- **XNLI** — Cross-lingual natural language inference (15 languages)
+- **XStoryCloze** — Story completion (11 languages)
+- **TyDi QA** — Question answering (11 languages)
+- **MMLU** — Multilingual knowledge
+
+## Related Resources
+
+- **Models**: [Legesher/language-decoded-lora](https://huggingface.co/Legesher/language-decoded-lora) — LoRA adapters trained on these conditions
+- **Community code**: [Legesher/language-decoded-community](https://huggingface.co/datasets/Legesher/language-decoded-community) — Human-written native language code
+- **Experiments**: [Legesher/language-decoded-experiments](https://huggingface.co/datasets/Legesher/language-decoded-experiments) — Training logs and eval results
+- **Paper**: Coming soon
+
+## Citation
+
+```bibtex
+@misc{language-decoded-2026,
+  title={Language Decoded: Investigating Language-Dependent vs. Structure-Dependent Reasoning Benefits of Code},
+  author={Madison Edgar and Saad Bazaz and Rafay Mustafa and Sarah Jawaid and Rashik Shahjahan and Khojasteh Mirza and Sohaib Bazaz},
+  year={2026},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/Legesher/language-decoded-data}
+}
+```
+
+## License
+
+Apache 2.0