Instructions to use KM4STfulltext/SSCI-BERT-e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KM4STfulltext/SSCI-BERT-e4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KM4STfulltext/SSCI-BERT-e4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KM4STfulltext/SSCI-BERT-e4") model = AutoModelForMaskedLM.from_pretrained("KM4STfulltext/SSCI-BERT-e4") - Notebooks
- Google Colab
- Kaggle
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## Cited
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- If our content is helpful for your research work, please quote our research in your article.
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## Disclaimer
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- The experimental results presented in the report only show the performance under a specific data set and hyperparameter combination, and cannot represent the essence of each model. The experimental results may change due to random number seeds and computing equipment.
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## Cited
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- If our content is helpful for your research work, please quote our research in your article.
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- https://link.springer.com/article/10.1007/s11192-022-04602-4
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## Disclaimer
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- The experimental results presented in the report only show the performance under a specific data set and hyperparameter combination, and cannot represent the essence of each model. The experimental results may change due to random number seeds and computing equipment.
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