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LLMAEL-ReFinED-FT
THU-KEG/LLMAEL-ReFinED-FT
LLMAEL-ReFinED-FT is a machine learning model from THU-KEG. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Jul 14, 2024
- Updated
- Jul 14, 2024
- SHA
- d4d19133
Model card
From the Hugging Face model README
Model Card for LLMAEL-ReFinED-FT
<p align="justify">We introduce <b>LLMAEL</b> (<b>LLM</b>-<b>A</b>ugmented <b>E</b>ntity <b>L</b>inking), a pipeline method to enhance entity linking through LLM data augmentation. We release our customly fine-tuned <b>LLMAEL-ReFinED-FT</b> model, which is fine-tuned from the <b>ReFinED</b> EL model using an <b>Llama-3-70b</b> augmented version of the <b>AIDA_train</b> dataset. LLMAEL-ReFinED-FT yields new SOTA results across six standard EL benchmarks: AIDA_test, MSNBC, AQUAINT, ACE2004, WNED-CLUEWEB, and WNED-WIKIPEDIA, achieving an average 1.21% accuracy gain.
For more details, refer to our paper 📖 LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking
</p>Model Description
- Developed by: Amy Xin, Yunjia Qi, Zijun Yao, Fangwei Zhu, Kaisheng Zeng, Bin Xu, Lei Hou, Juanzi Li
- Model type: Entity Linking Model
- Language(s): English
- Finetuned from model [optional]: ReFinED
- Library
- transformers
- Languages
- en
- Created
- Jul 14, 2024
- Updated
- Jul 14, 2024