Datasets:

PoSTMEDIA
/

rosetta-ko-code-synth-sft

language:
  - ko
license: apache-2.0
task_categories:
  - text-generation
  - question-answering
pretty_name: Rosetta KO Code Synthetic (SFT)
size_categories:
  - 100K<n<1M
tags:
  - korean
  - synthetic
  - rosetta
  - code
  - sft
extra_gated_prompt: >-
  By clicking "Agree" I confirm I have read and agree to the PoSTMEDIA Data
  Agreement for Model Training and agree that I intend to use this data for
  model training purposes only.
extra_gated_fields:
  Company: text
  Institutional Email: text
  Intended use: text
  I agree to use this dataset for model training purposes ONLY: checkbox
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl

rosetta-ko-code-synth-sft

Korean-native coding data — problems with solutions whose unit tests were actually executed and passed (execution-grounded rejection sampling).

Synthetic data generated with the Qwen3.6-27B teacher model — part of the Rosetta-KO suite for the Rosetta Korean LLM (PoSTMEDIA).

Code Suite

Sibling datasets from the same pipeline (each a separate repo):

repo	format
`rosetta-ko-code-synth-sft` (this repo)	supervised fine-tuning (user/assistant `messages`)
`rosetta-ko-code-synth-sft-think`	reasoning SFT (`<think>` chain-of-thought)
`rosetta-ko-code-synth-dpo`	preference pairs (`chosen`/`rejected`)
`rosetta-ko-code-synth-dpo-think`	reasoning preference pairs
`rosetta-ko-code-synth-rlvr`	reinforcement-learning-with-verifiable-reward rows

Data Fields

{"id": "...", "source_dataset": "...", "domain": "code",
 "messages": [{"role": "user", "content": "..."},
              {"role": "assistant", "content": "..."}]}

id — row-level identifier
messages[0] (user) — self-contained Korean prompt
messages[1] (assistant) — the answer directly (no reasoning trace)

Usage

from datasets import load_dataset
ds = load_dataset("PoSTMEDIA/rosetta-ko-code-synth-sft", split="train")

License

Released under the Apache License 2.0.

Seed sources:

Citation

@misc{rosetta_ko_code_synth,
  title  = {Rosetta-KO Code Synthetic Dataset},
  author = {PoSTMEDIA},
  year   = {2026},
  howpublished = {Hugging Face: PoSTMEDIA/rosetta-ko-code-synth-sft}
}

Contact

PoSTMEDIA — https://huggingface.co/PoSTMEDIA