A 995-example reasoning distillation dataset generated using the Google Gemma-4-31B-IT model as a teacher. The dataset was created by author trjxter and last updated on May 17, 2026. Each example is formatted for supervised fine-tuning, containing reasoning steps and a final answer.
Use Cases
- Fine-tuning language models for chain-of-thought reasoning based on the structured reasoning examples.
- Training models to follow specific output formats based on the ...tagging schema.
- Studying knowledge distillation techniques based on examples generated by a teacher model.
- Benchmarking model performance on single-turn reasoning tasks based on the dataset's domain and meta fields.
Strengths
- Contains 995 specific examples for supervised fine-tuning.
- Examples are generated by a known teacher model, Google's Gemma-4-31B-IT.
- Data uses a defined schema with fields for id, conversations, input, output, domain, and meta.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- trjxter
- Collection Method
- Generated via reasoning distillation using the google/gemma-4-31B-it model as a teacher.
- Time Range
- null
- Freshness
- Last updated 2026-05-17 02:17:17; freshness should be verified.
- Geography
- null