Instructions to use NorGLM/Entailment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NorGLM/Entailment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NorGLM/Entailment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NorGLM/Entailment") model = AutoModelForSequenceClassification.from_pretrained("NorGLM/Entailment") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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ent_ratio, neu_ratio, con_ratio = entailment_score(articles, references, hypo_list)
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```
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ent_ratio, neu_ratio, con_ratio = entailment_score(articles, references, hypo_list)
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```
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## Citation Information
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If you feel our work is helpful, please cite our paper:
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```
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@article{liu2023nlebench+,
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title={NLEBench+ NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian},
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author={Liu, Peng and Zhang, Lemei and Farup, Terje Nissen and Lauvrak, Even W and Ingvaldsen, Jon Espen and Eide, Simen and Gulla, Jon Atle and Yang, Zhirong},
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journal={arXiv preprint arXiv:2312.01314},
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year={2023}
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}
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```
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