synthetic data kit

We have hosted the application synthetic data kit in order to run this application in our online workstations with Wine or directly.

Quick description about synthetic data kit:

Synthetic Data Kit is a CLI-centric toolkit for generating high-quality synthetic datasets to fine-tune Llama models, with an emphasis on producing reasoning traces and QA pairs that line up with modern instruction-tuning formats. It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. The kit’s design goal is to shorten the “data prep” bottleneck by turning dataset creation into a repeatable pipeline rather than ad-hoc notebooks. It supports generation of rationales/chain-of-thought variants, configurable sampling, and guardrails so outputs meet format constraints and quality checks. Examples and guides show how to target task-specific behaviors like tool use or step-by-step reasoning, then save directly into training-ready files.

Features:

• Four-stage CLI pipeline from ingest to export
• Generation of QA pairs and reasoning traces
• Configurable prompting, sampling, and filters
• Training-ready output formats for fine-tuning
• Quality checks and schema validation
• Examples targeting task-specific reasoning

Programming Language: Python.
Categories: