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@@ -17,4 +17,23 @@ in https://github.com/hiyouga/ChatGLM-Efficient-Tuning/tree/main
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  CUDA_VISIBLE_DEVICES=3 nohup python src/web_demo.py \
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  --model_name_or_path /HOME/jack/model/chatglm-6b \
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  --checkpoint_dir paper_meta\ \
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- > log_web_demo.txt 2>&1 & tail -f log_web_demo.txt
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  CUDA_VISIBLE_DEVICES=3 nohup python src/web_demo.py \
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  --model_name_or_path /HOME/jack/model/chatglm-6b \
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  --checkpoint_dir paper_meta\ \
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+ > log_web_demo.txt 2>&1 & tail -f log_web_demo.txt
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+
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+
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+
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+ ### 🚩Citation
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+
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+ Please cite the following paper if you use OceanBench in your work.
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+
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+ ```bibtex
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+ @INPROCEEDINGS{10412837,
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+ author={Guo, Menghao and Wu, Fan and Jiang, Jinling and Yan, Xiaoran and Chen, Guangyong and Li, Wenhui and Zhao, Yunhong and Sun, Zeyi},
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+ booktitle={2023 IEEE International Conference on Knowledge Graph (ICKG)},
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+ title={Investigations on Scientific Literature Meta Information Extraction Using Large Language Models},
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+ year={2023},
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+ volume={},
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+ number={},
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+ pages={249-254},
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+ keywords={Measurement;Knowledge graphs;Information retrieval;Data mining;Task analysis;information extraction;large language model;scientific literature},
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+ doi={10.1109/ICKG59574.2023.00036}}
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+ ```