Instructions to use GE-Lab/SDGs-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GE-Lab/SDGs-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GE-Lab/SDGs-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GE-Lab/SDGs-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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If you use this model in your research, please cite our paper:
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```bibtex
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@article{Miyashita2025,
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author = {Naoto Miyashita and Takanori Matsui and Chihiro Haga and Naoki Masuhara and Shun Kawakubo},
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title = {Bridging the Sustainable Development Goals: A Multi-Label Text Classification Approach for Mapping and Visualizing Nexuses in Sustainability Research},
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If you use this model in your research, please cite our paper:
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```bibtex
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@article{Matsui2022,
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title={A natural language processing model for supporting sustainable development goals: translating semantics, visualizing nexus, and connecting stakeholders},
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author={Matsui, Takanori and Suzuki, Kanoko and Ando, Kyota and Kitai, Yuya and Haga, Chihiro and Masuhara, Naoki and Kawakubo, Shun},
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journal={Sustainability Science},
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volume={17},
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number={3},
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pages={969--985},
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year={2022},
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doi={10.1007/s11625-022-01093-3},
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publisher={Springer}
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}
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@article{Miyashita2025,
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author = {Naoto Miyashita and Takanori Matsui and Chihiro Haga and Naoki Masuhara and Shun Kawakubo},
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title = {Bridging the Sustainable Development Goals: A Multi-Label Text Classification Approach for Mapping and Visualizing Nexuses in Sustainability Research},
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