Shypd.aiThe largest open index of AI toolsGraphGen is an AI tool that enhances supervised fine-tuning for LLMs by generating knowledge-driven synthetic data. It constructs fine-grained knowledge graphs and identifies knowledge gaps to prioritize high-value QA pair generation.
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GraphGen is a comprehensive framework designed to enhance supervised fine-tuning (SFT) for Large Language Models (LLMs) through knowledge-driven synthetic data generation. It operates by first constructing detailed knowledge graphs from source texts, then identifying knowledge gaps in LLMs using calibration error metrics. This process prioritizes the generation of high-value, long-tail knowledge QA pairs. GraphGen further incorporates multi-hop neighborhood sampling to capture complex relational information and employs style-controlled generation to diversify the resulting QA data. After data generation, users can leverage tools like LLaMA-Factory and xtuner for LLM fine-tuning. The framework supports various LLM inference servers, API servers, inference clients, and input/output data formats, including PDF, JSON, and CSV, as well as databases like UniProt and NCBI.
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