All Tools
D
Fine-tuningFreeOpen Source
DISTILABEL
Synthetic data and AI feedback for LLMs
Apache-2.0
ABOUT
Creating high-quality training data for fine-tuning LLMs requires complex pipelines combining human feedback, synthetic data generation, and model evaluation. Distilabel provides a scalable framework for building AI feedback pipelines that generate, filter, and refine datasets using techniques from verified research papers, enabling faster and more reliable fine-tuning workflows.
INSTALL
pip install distilabelINTEGRATION GUIDE
1. Synthetic data generation: create high-quality training datasets using LLM-as-a-judge and self-instruct techniques
2. AI feedback pipelines: build scalable pipelines for annotation, preference collection, and model evaluation
3. Fine-tuning data curation: filter, deduplicate, and refine datasets for supervised fine-tuning and RLHF workflows
TAGS
synthetic-datafine-tuningai-feedbackdata-pipelinellmtraining-datadataset-creation