# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("morenolq/thext-cs-scibert")
model = AutoModelForSequenceClassification.from_pretrained("morenolq/thext-cs-scibert")General Information
This model is trained on journal publications of belonging to the domain: Computer Science.
This is an allenai/scibert_scivocab_cased model trained in the scientific domain. The model is trained with regression objective to estimate the relevance of a sentence according to the provided context (e.g., the abstract of the scientific paper).
The model is used in the paper 'Transformer-based highlights extraction from scientific papers' published in Knowledge-Based Systems scientific journal. The model is able to achieve state-of-the-art performance in the task of highlights extraction from scientific papers.
Access to the full paper: here.
Usage:
For detailed usage please use the official repository https://github.com/MorenoLaQuatra/THExt .
References:
If you find it useful, please cite the following paper:
@article{thext,
title={Transformer-based highlights extraction from scientific papers},
author={La Quatra, Moreno and Cagliero, Luca},
journal={Knowledge-Based Systems},
pages={109382},
year={2022},
publisher={Elsevier}
}
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="morenolq/thext-cs-scibert")