Synthetic Coding Tasks with Verifiable Solutions and Tests

KodCode V1 is a fully-synthetic open-source dataset for coding tasks, containing 12 distinct subsets across domains like algorithmic and package-specific knowledge. It is designed for supervised fine-tuning and RL tuning, with difficulty levels ranging from basic exercises to competitive programming challenges.

Use Cases

• Fine-tune a code generation model on algorithmic tasks using the provided verifiable solutions and tests.
• Train a model for package-specific knowledge tasks across the 12 distinct dataset subsets.
• Use the dataset's difficulty levels, from basic to competitive programming, to benchmark model performance on coding challenges.

Strengths

• Contains 12 distinct subsets spanning various coding domains and difficulty levels.
• Provides verifiable solutions and tests for coding tasks.
• Designed for both supervised fine-tuning and RL tuning.

Limitations

• The dataset is fully synthetic, which may not fully represent real-world coding patterns or complexities.
• Specific details on the number of rows, columns, and file formats are unavailable for assessing scale and structure.

Provenance

Source

KodCode

Collection Method

Fully-synthetic generation.

Freshness

Last updated on 2025-03-17.