HKUDS/GraphGPT
[SIGIR'2024] "GraphGPT: Graph Instruction Tuning for Large Language Models"
This project helps researchers and data scientists working with complex graph data to integrate that data more effectively with large language models (LLMs). It takes graph-structured data (like networks of academic papers or biological interactions) and processes it so LLMs can 'understand' and reason about its connections. The output is a fine-tuned language model capable of performing tasks like node classification or link prediction within the graph context, making it useful for researchers analyzing networked information.
819 stars. No commits in the last 6 months.
Use this if you need to train a large language model to interpret and act upon the structural relationships present in your graph-based datasets.
Not ideal if your primary need is to analyze tabular data, image data, or unstructured text without any inherent graph structure.
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819
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80
Language
Python
License
Apache-2.0
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Last pushed
Jun 25, 2024
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