qwen_training_data_miner_prototype

To extract training data from a log file for instruction tuning, you need a data mining process that scans text for domain-specific patterns. This Skill automates extracting high-quality examples from 012.txt and outputs a structured JSON dataset.

Yes, you can automatically generate an instruction-tuning dataset from raw text logs. This Skill applies strict quality filtering to extract complete, unambiguous examples and structures them with metadata and recommended training configurations.

Pattern extraction for AI model training works by scanning log files to identify domain-specific examples, such as MPS scoring or WSP application. It converts these identified patterns into a structured format with input, output, and rationale.

The best way to filter high-quality examples for a JSON training dataset is to apply strict criteria ensuring only complete and unambiguous data is retained. This Skill automates that quality filtering during the log mining process.

Yes, this data mining approach specifically works for extracting MPS scoring and WSP application examples. It scans the 012.txt log file for these defined knowledge domains to generate targeted instruction-tuning data.

To start mining 012.txt for AI model training data, you simply need the target log file available. The Skill autonomously scans the file, extracts verifiable data, and outputs a ready-to-use JSON dataset with execution instructions.