How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="Fredr0id/proquolm")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Fredr0id/proquolm")
model = AutoModelForSequenceClassification.from_pretrained("Fredr0id/proquolm", device_map="auto")
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Model Summary

This model is a finetuned bert-base-german-uncased for binary classification of short quotations between literary works and scholarly works. The model is intended to be used as part of our tool ProQuoLM. More information can be found in the corresponding repository and our paper A Novel Approach for Identification and Linking of Short Quotations in Scholarly Texts and Literary Works.

Citation

@article{arnold2023,
  author = {Frederik Arnold, Robert Jäschke},
  title = {A Novel Approach for Identification and Linking of Short Quotations in Scholarly Texts and Literary Works},
  volume = {2},
  year = {2023},
  url = {https://jcls.io/article/id/3590/},
  issue = {1},
  doi = {10.48694/jcls.3590},
  month = {1},
  publisher={Universitäts- und Landesbibliothek Darmstadt},
  journal = {Journal of Computational Literary Studies}
}
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