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dataset-curation

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About dataset-curation

D

dataset-curation

Prepare, format, and validate datasets

dataset-curation is an agent skill from the wshobson/agents collection for preparing, formatting and validating datasets used to fine-tune language models, with supervised fine-tuning (SFT) and preference training as the main cases. It takes raw examples, such as demonstrations, preference judgments or task prompts, and turns them into a formatted, packed and validated JSONL dataset. The skill explains how the required format depends on the training method that was chosen, covers the template and packing mechanics behind the most common silent training failures, and sets rules for mixing synthetic data into a dataset without causing the model to collapse. It ends with a dataset card, a record of what the data is and how it was built, which the wider fine-tuning workflow uses as a gate before a training run starts. The skill assumes the training method has already been chosen, so it sits after the routing step in the wshobson fine-tuning sequence and is not a method selector. It is installed with the skills CLI from the wshobson/agents repository. Its skills.sh page showed about 2.4K installs and passing results from three security audits at the time of the scan.

View dataset-curationAll AI Skills apps
Price
Free
Made by
wshobson
Category
AI Skills
Website
github.com/wshobson/agents/dataset-curation